<![CDATA[Heartcore Insights]]>https://heartcore.substack.comhttps://substackcdn.com/image/fetch/$s_!o4Ku!,w_256,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F6674842a-73e1-4934-8f35-1181f1c76cbe_155x155.pngHeartcore Insightshttps://heartcore.substack.comSubstackFri, 19 Jun 2026 09:29:07 GMT<![CDATA[🎉 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-3c1https://heartcore.substack.com/p/heartcore-insights-3c1Thu, 28 May 2026 07:16:03 GMT

Hi there,

Welcome to the 138th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Welcome Naza Metghalchi to Heartcore!

Today, we are stoked to officially welcome Naza Metghalchi to Heartcore Capital as Partner! 🔥

Naza has spent her career around ambitious people building movements before the rest of the world fully understands them. From political systems to startups, she has always been drawn to conviction, speed and obsessive belief.

She joins us from EQT Ventures, where she backed founders across the B2B AI transition and built a reputation for backing exceptional people early.

She deeply aligns with how we think about investing from inception at Heartcore: believing in exceptional people long before the evidence arrives.

She also spent a surprising amount of time stress-testing one particular Heartcore value: Love. Safe to say, she eventually got stuck with it. ❤️‍🔥

Hear from Naza herself on her journey, investment philosophy and how she works with founders from the earliest stages 👇🏻

Physical AI: Three Tailwinds, One Inflection Point

There are moments in technology where several things align at once. In Physical AI, three shifts that would each independently excite investors are happening simultaneously: a migration of world-class talent from research labs to commercial ventures, a series of compounding technology breakthroughs and structural tailwinds that are pulling the entire ecosystem forward.

We have been tracking this space closely, and the pace of change over the past twelve months has been unlike anything we have seen before in robotics.

The talent signal is unmistakable. Academic research in robotics has increased exponentially, and the best researchers are no longer staying in labs - they are founding companies. Physical Intelligence, started by former Google DeepMind researchers, is raising $1B at an $11B valuation. Skild AI closed $1.4B in January. In Europe, Germany’s NEURA Robotics raised $1.2B in March, becoming the continent’s most funded humanoid robotics company, and launched Europe’s largest scientific training centre for Physical AI - TUM RoboGym. This pattern of talent exodus from academia into startups mirrors everything we have seen in previous inflection points - and historically, once the talent moves, the market follows.

The hardware economics are shifting fast with the most consequential shift in edge compute. Ten years ago, $500 bought you roughly 1 TOPS (trillions of operations per second) of edge compute capability. Today, NVIDIA’s latest Jetson chips deliver +2,000 TOPS - a 2,000x performance improvement at only a 7x increase in price. This matters because Physical AI demands real-time intelligence. A chatbot can tolerate a half-second delay; a surgical robot or an autonomous vehicle cannot. Intelligence has to live on the robot itself.

This creates an interesting dynamic that separates Physical AI from digital-based AI. Robots are battery-constrained, thermally constrained and latency-constrained systems. You cannot simply deploy ever-larger models. Instead, the industry is being pushed toward smaller, faster, more efficient models - and toward more open ecosystems. NVIDIA’s GR00T N1 foundation model for humanoids is open-source and integrated with Hugging Face. Cosmos provides synthetic data and world modelling. Isaac Sim enables large-scale simulation. The infrastructure players benefit when more teams experiment and deploy, and that is accelerating the entire space.

This is also creating opportunities for a new infrastructure layer around Physical AI. Companies like Qualia 🖤, which we backed last year, are building the developer tooling robotics teams to work across different models, and environments. As experimentation accelerates, interoperability and workflow abstraction may very well become one of the most important layers.

But let’s be intellectually honest: robotics is still hard. Generalisation remains a fundamental challenge - a warehouse robot trained on one box shape may fail when packaging or lighting changes. Manipulation requires hardware breakthroughs as much as software ones. And unlike LLMs, there is no internet-scale dataset for robotics. Data collection is expensive, embodiment-specific, and often proprietary. Lastly there is the whole issue around “catastrophic forgetting” - when a robot learns to navigate a new kitchen layout, it risks overwriting the skills it previously mastered elsewhere, because memory and learned knowledge are encoded in the same model weights. Future architecture will need to separate long-term memory from core reasoning, but we are not there yet.

The emerging paths are promising. World models - neural networks trained on massive amounts of video that learn physical intuition - are showing early results. Meta’s V-JEPA 2 achieved 80% zero-shot success on real robot arms with just 62 hours of robot-specific data. Simulation and RL work well for locomotion. And the gap between demonstration and deployment is genuinely closing: Figure AI went from producing one robot per day to one per hour at its BotQ facility, and 1X’s consumer humanoid NEO sold out its first-year production run of 10,000 units in five days.

Where does this leave us as investors? We believe open-source will commoditise model architectures faster than most expect, but the data and deployment layers will remain proprietary long enough to matter. The companies that understand which parts of their stack to open and which to protect will have a meaningful strategic advantage. Commercial adoption is emerging fastest in constrained, vertically specialised environments - healthcare, industrial automation, defence, autonomous vehicles – closed loops, where robots do not need to do everything, they need to do one thing reliably.

Robotics may not be having its ChatGPT moment just yet. Our bar for what is “good enough” for a robot remains orders of magnitude higher than for a chatbot. But the convergence of talent, declining hardware costs, exponentially improving edge compute and open infrastructure is creating the conditions for something significant.

As always, if you are building in this space, we would love to talk.

~Lærke Hansen, Investor, Heartcore Capital

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]]><![CDATA[🔐 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-95ahttps://heartcore.substack.com/p/heartcore-insights-95aTue, 28 Apr 2026 08:20:11 GMT

Hi there,

Welcome to the 137th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Brief Market Commentary

Crypto’s Fear & Greed index has clawed its way back to neutral after its Feb dip to multi-year lows. And every macro pundit has, once again, mistaken six weeks of price action for regime change.

We keep coming back to Amara’s Law: humans overestimate change in the short term and underestimate it in the long term. The list of things being mispriced on exactly that axis is getting longer. Energy prices (cheap forever or expensive forever, depending on the week). European sovereignty (a slogan in 2022, a procurement line item in 2026). Stablecoin rails (a meme three cycles ago, rivaling Visa in settlement volume today). Add agentic commerce, post-quantum security, the nuclear renaissance, the quiet reindustrialization of the continent and the tokenization of real-world assets. Each looks like noise this quarter and inevitability by 2033.

Which is why we keep returning to an old line: in the short run, the market is a voting machine; in the long run, it is a weighing machine. Blitzscaling has been an excellent way to torch capital over the past decade. Patient, systematic capability building (the unsexy, compounding kind) in the startup journey is what the weighing mechanic eventually rewards. And hence we would rather be early to the weighing than loud at the voting.

~Max Niederhofer, Partner, Heartcore Capital

Crypto is Dead, Long Live Blockchain

Anyone looking at crypto these days must feel the structural changes of the industry. OGs are in complete dismay while fintech and regulators are excited about the prospects of stablecoins, 24/7 trading and immutability of the underlying ledgers. We wanted to take the time to shed some light on what’s happening.

Fear & Greed Index is at all-time-lows

The crypto industry is being reborn, and the resulting split is healthy. On one side (the side OGs have known for the better part of two decades), the industry is contracting. It is the wild west known for anonymous founders launching useless tokens full of promises, retail investors chasing asymmetric returns and product-market fit hiding behind heavily incentivised private deals.

The other side of the split looks nothing like this. Blockchain technology, dressed in compliance and applied to real problems, is attracting a new and very different class of attention and excitement. We see historically non-crypto investors such as Accel (OpenFX’s $23M round), Creandum (Midas’s $50M Series A round), Franklin Templeton (Midas, $7.5M seed round for Cap stablecoin) or institutional banks ($136M Series C round of Fnality) write checks into the technological unlock that existing rails cannot match: settlement in seconds, cross-border transactions without correspondent banking intermediaries, programmable compliance built directly into the asset layer and cost structures that reduce operational overhead by an order of magnitude.

But Why are Non-Crypto Investors Moving into the Space Now?

The core driver of this shift is not technology; this technology has existed for years. It is regulation. The US GENIUS Act, signed into law in 2025, created the first federal framework for stablecoins and the US CLARITY Act working its way through the Senate is set to form clarity for the security/commodity classification of tokens, while the EU’s MiCA is actively reconfiguring usage patterns across Europe. The era of operating in a legal grey zone is functionally over, which inevitably leads to more accountability across the space.

The industry stakeholders sarcastically say that ‘token is the real product’ but it is also the major driver of failure within this industry. Governance tokens in their grey-zone regulatory treatment amplify short-term incentive thinking, misaligning both founder (“let me launch a token so that I can exit in 12 months instead of building for 10 years”) and user interests (“let me use this product so that I can get free money in a form of a token, not because I’d actually need this”).

Accountability flushes this behaviour. It also changes the initial value proposition of techno-anarchism the early adopters fell in love with. The result is the same. Some are leaving voluntarily (in 2025, we have seen some of the largest distributions on record from long-term holders); others are being pushed out. Both are making room for operators who are here to build long-term.

How do we Position ourselves in this New Paradigm?

The old “crypto” will not die, but it will contract to irrelevance. Instead, the technology will shine and the financial industry will be the main benefactor: trading, lending, payments and capital formation on blockchain rails; these protocols are already generating real revenue at scale and earning institutional trust. Tokens will continue to exist, but the industry will converge toward clear, standardised token structures with tokens and equity gradually merging into a single instrument with clearly defined rules and value-accrual mechanisms.

We already see a case study for such tokens in our largest portfolio company, Hyperliquid 🖤. Hyperliquid’s HYPE token behaves like equity, capturing all protocol economics, and it benefits greatly, while altcoins declined 40-60% in Q1, Hyperliquid rallies 51% at the same time. The market is sending an unmistakable message: either you put token holders first or you don’t get any holders.

So where exactly are we spending our time taking advantage of this shift? We look for investments within a few, selective areas:

  • B2B capital markets infrastructure, particularly tokenization of difficult-to-access real-world assets, which is already a $185B market today and projected to reach $30T by 2030,

  • Agentic payments, where AI agents transacting autonomously demand a settlement layer that legacy fiat rails cannot provide,

  • Post-quantum security solutions that protect blockchain immutability and the fintech future we envision,

and builders who understand the new paradigm we are moving into.

If you are a builder or you know anyone building with this thesis in mind, we would love to chat!

~Tomas Fanta, Investor, Heartcore Capital

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]]><![CDATA[🌍 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-277https://heartcore.substack.com/p/heartcore-insights-277Tue, 31 Mar 2026 08:04:21 GMT

Hi there,

Welcome to the 136th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

Going forward, we will share short commentary from our Partner team on the markets shaping European tech and venture. Let us know what you think about the new format.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Brief Market Commentary

Day 90 of 2026 (only). Day 437 of Trump 2.0 (70% of term remaining).

The third energy crisis for Europe in recent memory (pandemic + Ukraine + Iran). And yet… “geopolitics don’t always matter in the way that market participants expect”…

Despite the confluence of political, technological and economic moments of maximum uncertainty, there is palpable excitement in the Euro VC market about the diffusion of AI and progress in quantum technologies. We are seeing a steepening of the power law, where the top 5% of companies can raise almost unlimited capital. For the rest, it is a long, steady build and capital availability seems more similar to historical average.

We think this is a good thing as we have always preferred long-term compounding over blitzscaling, not least to limit dilution for founders.

~Max Niederhofer, Partner, Heartcore Capital

Why Did We Invest in EGIDE?

Investing in defence is not neutral. It forces you to take a position, implicitly or explicitly, on what role technology should play in conflict.

For a long time, we were not comfortable crossing that line.

And yet, last week we announced our participation in EGIDE’s €8M Seed round. It is our first investment in defence at Heartcore Capital.

A New Era of Warfare, and a European Paradox

The war in Ukraine has made something very visible: we have entered a new era of warfare. Cheap, mass-produced system, particularly drones, can now overwhelm highly sophisticated and expensive defence infrastructures.

Shahed drones cost $20-30k and can be produced in days. They are used for saturation, not precision.

On the other side, interception systems such as Patriot missiles can cost millions per shot and take months to produce. Even when interception works, the economics don’t.

This shift has exposed a structural imbalance, and Europe is not ready.

Despite rising defence budgets, many systems remain designed for a different era. Recent incidents: from unidentified drones near major infrastructure to repeated airspace violations in countries like Poland and Romania, highlight a recurring issue: slow response times, unclear attribution and inconsistent interception capabilities. Europe is already being tested at the margins.

From Ethical Hesitation to Investment Conviction

For a long time, this translated into a real hesitation on our side, not only from a pure “investor” standpoint, but also an ethical one.

Defence comes with everything venture capital tends to avoid: long sales cycles, concentrated customers, complex procurement processes and unclear exit paths.

But over time, a different picture emerged.

Europe faces a structural innovation gap, driven by years of underinvestment, and combined with a renewed willingness from governments and stakeholders to support new players. And precisely because the space is so difficult, it creates strong barriers to entry for the teams that can navigate it.

Why EGIDE

This is where EGIDE stood out.

Simon and Florian both from MBDA, have spent years building complex defence systems from the inside. They understand not only how these systems work but where they break.

Florian Audigier and Simon Calonne (Founders of EGIDE)

Their core insight is that the issue is not just cost, it’s how these systems are built, with architectures that make them hard to iterate, scale or adapt.

Traditional systems are hardware-first, optimised for performance but not for iteration or scale. EGIDE takes the opposite approach: a software-defined platform, where guidance, sensing and control are modular, enabling faster adaptation and scalable deployment.

At the core is Mystique, a hardware-agnostic platform integrating sensors, AI-driven detection and layered response capabilities.

EGIDE is not building a single product, but a platform designed to evolve into a broader family of systems, and ultimately a new kind of defence company.

What convinced us most was the team. They combine a rare technical depth with a clear vision of what needs to be built, in what order and why.

Europe is entering a new phase, where security and sovereignty are central again. This will require not just more capital, but new types of companies that are faster, more adaptable and built of modern conflict.

We believe EGIDE is one of the first credible teams in Europe attempting to do exactly that.

And we are proud to support them!

As always if you are building in this space, we’d love to talk.

~Bérenger Teboul-Danguin, Associate, Heartcore Capital

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]]><![CDATA[✨ Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-fdbhttps://heartcore.substack.com/p/heartcore-insights-fdbThu, 26 Feb 2026 13:02:46 GMT

Hi there,

Welcome to the 135th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Reinforcement Learning is Re-writing AI, and Europe has a Seat at the Table

For most of the half-decade, the story of AI progress was simple: make the model bigger, feed it more data and performance improves. However, recent frontier models are posting smaller benchmark gains despite eye-watering compute budgets and high-quality training data is running out. Anthropic CEO Dario Amodei said in 2025, “two years ago, we thought there was this fundamental obstacle around reasoning. Turned out just to be RL.”

Reinforcement learning is the second scaling axis that pre-training alone couldn’t provide, generating its own training signal through feedback rather than consuming ever more human-written data.

A 70-year-old Idea whose Moment has Arrived

RL isn’t new. Richard Bellman laid its foundations in the 1950s, Sutton and Barto formalised temporal-difference learning in the 1980s which won the 2025 Turing Award for that foundational work (and humbled Dwarkesh in a podcast appearance last year).

DeepMind’s 2013 Atari paper reignited it, AlphaGo shocked the world in 2016, and AlphaFold earned the 2024 Nobel Prize in Chemistry. Still, these were domain-specific wins.

The real unlock came when RL collided with language models. Standard language models learn by predicting the next word, sophisticated pattern matching at enormous scale. That works well, but it has a ceiling. You can’t pattern-match your way to solving a hard math problem you’ve never seen before and pre-training, by itself, teaches imitation rather than teaching reasoning.

RL changes the equation fundamentally. At its core, RL is about trial and error. An agent tries things, gets rewarded or penalised at the end of its run (up or down weighted), and gradually learns what works.

Instead of imitating human text, models trained with RL learn to reason toward correct answers, verified against objective outcomes like code that compiles, proofs that check out, or answers that match a ground truth. This approach, called Reinforcement Learning from Verifiable Rewards (RLVR), generates training signals automatically with no human annotators needed. Less dependence on curated data, less reliance on ever-larger pretrained models. This gets a little more tricky for non-verifiable tasks, where the fall-back are basically judge models trained from RLHF, RLAIF or other methods, but the principle still remains.

From Research Labs to Enterprise

Europe has the chance to be a leader in the space:

Paris-based Adaptive ML has built a dedicated RLOps platform already deployed by AT&T and SK Telecom.

Mistral’s Magistral confirmed in recent research, that a moderately-sized model fine-tuned with a single phase of RL on the right domain can consistently outperform larger general-purpose models. A 14B parameter model trained with RL on biological reasoning can outperform GPT-4 class models on those tasks at a fraction of the inference cost.

DeepMind’s RL system cut Google’s data centre cooling costs by 40%.

London’s InstaDeep (acquired by BioNTech for £562M) identified 12 of 13 WHO-flagged COVID variants two months ahead of official designation.

Wayve raised $1.2B in early 2026 at an $8.6B valuation, training autonomous vehicles with end-to-end RL across 500+ cities.

Mistral AI raised €2B with RL-based reasoning models. On the emerging side, Isomorphic Labs is applying RLVR to drug discovery and a flood of startups are addressing “RL for code generation”, thanks to tight verifiable feedback loops, and recommendation systems are being rebuilt around long-horizon reward signals rather than clicks.

And countless more very promising early-stage companies across Europe.

Emerging RL Categories Worth Watching

RL for code has already gone mainstream due to tight feedback loop and clear verifiable objectives, making it one of the cleanest domains for RL to shine. Beyond the obvious use cases, several newer RL applications are gaining serious traction:

Multi-agent RL, systems where multiple agents learn to coordinate in real time, is moving into logistics, energy grids and autonomous fleets.

Scientific discovery is arguably the most exciting frontier. RLVR-trained agents are now automating multi-step research tasks (hypothesis generation, experimental design, data analysis) using computational verification as the reward signal.

Personalisation and recommendation systems are getting an RL refresh too. Rather than optimising for click-through rates, next-generation systems are training agents with long-horizon reward signals (user retention, satisfaction and real-world outcomes) producing qualitatively different behaviour to traditional recommendation algorithms. Next will be real world simulation and feeding it as behavioural context into world models.

Bottomline: RL is having a moment (again, or still?), and Europe should be the main stage! As always if you are building in this space, we’d love to talk.

~ Bodi Tent, Associate, Heartcore Capital

🇪🇺 Notable European early-stage rounds

  • Paraglide, a Sweden-based agentic AI startup focused on accounts receivable, raises $5M with Bessemer Ventures - link

  • Co-reactive, a Germany-based developer of CO2-negative materials tech, raises €6.5M with HTGF - link

  • Electric Twin, a UK-based developer of synthetic audiences, raises $10M with Atomico/LocalGlobe - link

  • Capalo AI 🖤, a Finland-based battery storage and renewable asset optimiser, raises €11M with Heartcore Capital/Tesi - link

  • Stacks, a Netherlands-based agentic platform for enterprise finance, raises $23M with Lightspeed - link

  • Duna, a Netherlands-based AI-native business identity platform, raises €30M with CapitalG - link

  • Onodrim Industries, a Netherlands-based defence-tech and supply resiliency startup, raises €40M with FoundersFund/Lakestar - link

🇺🇸 Notable US early-stage rounds

  • Sapiom, a startup providing financial infrastructure for autonomous AI transactions, raises $15M with Accel - link

  • Moab, an equipment rental and dealership software developer, raises $16M with Elad Gil - link

  • Meridian, a provider of AI-powered workspace for financial modeling, raises $17M with A16Z - link

  • Complyance, a provider of AI agents that automate enterprise governance and compliance, raises $20M with Lightspeed - link

  • Pasito, a workspace for group health, life and retirement benefits, raises $21M with Insight Partners - link

  • Lotus Health AI, a developer of AI doctors, raises $35M with CRV/Kleiner Perkins - link

  • Monaco, a provider of AI agents that automate enterprise sales workflows, raises $35M with FoundersFund - link

🔭 Notable later stage rounds

  • RobCo, a Germany-based developer of industrial robots, raises $100M with Lightspeed - link

  • Synthesia, a UK-based B2B AI video generation platform, raises $200M with GV - link

  • Runway, a US-based AI video startup, raises $315M with General Atlantic - link

  • ElevenLabs, a UK-based AI voice generation platform for creators and enterprises, raises $500M with Sequoia - link

  • Cerebras Systems, a US-based developer of wafer-scale AI chips and compute services, raises $1B with Tiger Global - link

  • Wayve, a UK-based builder of autonomous driving software and AI models, raises $1.2B with Eclipse/Balderton/SoftBank Vision - link

  • Databricks, a US-based cloud platform to build data and AI systems, raises $5B with Goldman Sachs - link

  • Waymo, a US-based autonomous robotaxi service operator, raises $16B with Dragoneer/DST/Sequoia - link

  • Anthropic, a US-based AI lab behind Claude, raises $30B with Dragoneer/ FoundersFund/ ICONIQ - link

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]]><![CDATA[🎊 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-ff3https://heartcore.substack.com/p/heartcore-insights-ff3Tue, 27 Jan 2026 09:00:35 GMT

Hi there,

Welcome to the 134th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

The Second Century of Quantum Won't Be Built in Silicon Valley

Driving back from Q2B Silicon Valley to the airport a month ago, I found myself surrounded by billboards. “Your AI SDR that never sleeps.” “Agentic workflows for enterprise.” “Deploy autonomous agents in minutes.” The usual Silicon Valley chorus. Meanwhile, inside the conference, John Preskill had just made a quiet but significant announcement: We are entering the second century of quantum.

What will this second century bring? Preskill’s answer was ambitious – the wonders we encounter may far surpass those of the first century. Yet nobody on the highway seemed to notice. This was the final Q2B conference in Silicon Valley. Next year, it moves to Chicago. The quantum revolution, it seems, isn’t happening where the silicon revolution began. Things change.

Where quantum is actually happening

The policy landscape tells the story. According to the OECD, 18 OECD member countries plus the EU have now adopted dedicated national quantum strategies. Global governments have committed an estimated $55.7B to quantum science and technology since 2013. The momentum is accelerating. According to OECD, international quantum patent families grew sevenfold between 2005 and 2024 – a 20% compound annual growth rate, compared to just 2% for all technologies combined.

The ECIPE quantum clusters ranking attempts to map where this activity concentrates, identifying 45 quantum clusters worldwide. The ranking places Cambridge, UK at #1, Helsinki, Finland at #2, Oxford, UK at #3. The ranking is directionally interesting, but I’d score some clusters differently. Chicago should rank significantly higher given the ecosystem forming there (hence the Q2B move). The Munich area and Delft deserve more prominence. Japan’s near-absence from the top rankings feels like a gap. Still, the report captures something important: the sheer breadth of places where quantum is being developed. This is not a one-city phenomenon.

This distribution is significant. Quantum isn’t following the playbook of software or even AI, where winner-take-all dynamics concentrate innovation in a few zip codes. The physics is too hard, the talent too specialised, the infrastructure too demanding. Progress happens where deep research institutions, precision manufacturing and patient capital converge – and those conditions exist in many places.

The data on Europe is particularly striking. According to the IE CGC report on Europe’s quantum readiness, Europe is building what no single nation can – continent-wide quantum infrastructure through EuroQCS for computing and EuroQCI for secure communications. The report’s expert panel rates Europe’s quantum competitiveness at 3-4 out of 5, with a clear trajectory toward what they call “A Sovereign Quantum Europe” by 2040.

From science to industry

As we argued in our earlier piece, the race isn’t about counting qubits, rather it is about building the infrastructure that will manufacture them at scale – and this is what the second century of quantum will be about.

Conferences like the ISIG Quantum Computing Infrastructure Summit are now addressing exactly this: manufacturing, scalability and the path to commercialisation. The Quantum Insider reached similar conclusions.

The question isn’t whether quantum will matter – it will. The question is where it will be built.

Wherever you are based, there are likely researchers, engineers and entrepreneurs building quantum around you. If you are one of them – whether working on hardware, enabling infrastructure or the software stack that will connect it all – we’d love to talk. We can help connect you to the broader ecosystem and think through where this goes next.

~ Michael Baczyk, Investor, Heartcore Capital

🇪🇺 Notable European early-stage rounds

  • Anzen Industries, a UK-based biomanufacturing startup focused on producing chemicals via cell-free enzymes, raises $2.2M with LocalGlobe - link

  • Stilla, a Sweden-based startup building AI-human collaborative decision infrastructure, raises $5M with General Catalyst - link

  • 24 Industries, a Germany-based drone-maker, raises $11.8M with Lakestar - link

  • Enodia Therapeutics, a France-based startup developing ML-driven targeted protein degradation platform, raises $25M with Bpifrance - link

🇺🇸 Notable US early-stage rounds

  • Formulary, an AI-native fund administrator, raises $4.6M with Khosla - link

  • Aurora, a personalised genetics medicine startup, raises $16M with Menlo - link

  • Converge Bio, a startup accelerating drug discovery with generative AI, raises $25M with Bessemer - link

  • Protege, a startup unlocking trusted real-world data at scale, raises $30M with A16Z - link

  • depthfirst, a startup building AI-powered cyber defence systems, raises $40M with Accel - link

🔭 Notable later stage rounds

  • Harmonic, a US-based startup building AI for mathematical reasoning, raises $120M with NVentures/Ribbit/Sequoia - link

  • Harmattan AI, a France-based startup developing autonomous, AI-driven drone and air-defence systems, raises $200M with Dassault Aviation - link

  • Pennylane, a France based fintech providing accounting and finance for SMEs, raises €175M with TCV/Blackstone - link

  • Terralayr, a Germany-based utility-scale battery storage platform, raises €192M with Eurazeo - link

  • OpenEvidence, a US-based AI medical search platform for clinicians, raises $250M with Thrive/DST - link

  • Mews, a Netherlands-based cloud native hospitality management system, raises $300M with EQT/Atomico - link

  • Parloa, a Germany based AI-powered customer service automation platform, raises $350M with General Catalyst - link

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]]><![CDATA[🤟🏻 Heartcore's 2025 Round-up]]>https://heartcore.substack.com/p/heartcores-2025-round-uphttps://heartcore.substack.com/p/heartcores-2025-round-upWed, 17 Dec 2025 08:15:38 GMT

2025 Round-up

💫 As the year comes to a close, it naturally invites reflection. A moment to pause before the calendar resets and the details start to blur.

In 2025, Heartcore Capital ranked among the Top 1% Power Law Investors in EMEA out of 3600+ EMEA funds and the Top 5% value-add investors out of 800+ EMEA funds, according to Dealroom.co. We value these recognitions not as scorecards, but as indicators of something earned over time: early conviction, close partnership, founders who kept building through a demanding market.

None of this happens in isolation. These outcomes are the result of relentless work by the founders we back, resilient teams across our portfolio and the trust our LPs place in us.

Alongside that, our community here has continued to grow, now more than 7,700 strong, engaging with our thinking, challenging our assumptions, staying curious with us.

What follows is a look back at the moments, progress and people that shaped 2025 and the foundations they have laid for the year ahead. Investing in Happiness remains at the core of how we operate and will continue to guide us into 2026. 🤟🏻

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

We saw fantastic fundraising across our portfolio…

…among several others in 🇪🇺 who we haven’t yet announced as they focus on building! Stay tuned for these announcements in 2026.

We saw them reach other sorts of milestones too…

We also welcomed some fantastic people to our team…

We hosted some wonderful events with our founders and our team…

We also took the stage / the mic, were quoted in and put out some thought pieces….

Thank you for being a loyal subscriber of our monthly Insights. Please feel free to share this newsletter with anyone you’d think would appreciate it!

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]]><![CDATA[Heartcore on Quantum]]>https://heartcore.substack.com/p/heartcore-on-quantumhttps://heartcore.substack.com/p/heartcore-on-quantumWed, 03 Dec 2025 08:02:26 GMT

Forget the Qubits

The Global Race Is On

One hundred years after quantum mechanics was born, 2025 ends on a radically different footing. The International Year of Quantum Science was supposed to be a celebration of science. Instead, it became the year quantum went industrial.

November 2025 wasn’t about any single announcement. It was about all of them happening at once. The US, Europe, China - each made decisive plays within weeks.

The US is accelerating. On November 6, DARPA selected 11 companies to enter Stage B of its Quantum Benchmarking Initiative, aiming to verify whether any quantum computing approach can achieve utility-scale operation, computational value exceeding cost, by 2033. On November 18, the U.S.-China Economic and Security Review Commission urged Congress to adopt a “Quantum First” national goal by 2030. The language is stark: “Whoever leads in quantum (and AI) will control the encryption of the digital economy, enable breakthroughs in materials, energy and medicine, and gain asymmetric and likely persistent advantage in intelligence and targeting.” That same week, the Pentagon elevated quantum to a central priority, framing “Quantum and Battlefield Information Dominance” as essential for communications and navigation that can withstand jamming on contested terrain. On November 25, President Trump launched the Genesis Mission, a DOE-led initiative linking supercomputers, AI and quantum systems to accelerate discovery and national security.

Europe’s push came fast and coordinated. I was at the European Quantum Technologies Conference in Copenhagen in November, where Commissioner Henna Virkkunen opened the event and made it unmistakably clear: quantum is the chance for Europe regarding her priorities on tech sovereignty, security, and democracy. Earlier this year, the Commission unveiled the Quantum Europe Strategy to turn scientific strength into economic scale. The Strategy aims to deliver: six quantum chip pilot lines under the Chips Joint Undertaking; the EuroQCI secure communication network across all member states by 2030, including the Eagle 1 satellite in 2026; a European Quantum Skills Academy launching in 2026; and supply-chain risk mapping across the quantum stack. The EU Quantum Act, set for adoption in 2026, targets three structural problems: fragmented research, industrial capacity gaps, and supply-chain vulnerabilities (Open call for evidence deadline: December 15). Last but not least, the EuroHPC Quantum Grand Challenge Call was announced (deadline: January 8, 2026) that invites European startups to develop quantum solutions with clear market perspectives, with successful participants advancing to European Investment Bank financing.

And China? The 14th Five-Year Plan (2021-2025) positions quantum as a central pillar of China’s deep tech ecosystem. Compared to the previous plan, quantum references tripled, expanding from communications to include computing and sensing, signaling a shift from experimentation to deployment. China’s quantum communications infrastructure remains unmatched: the Micius satellite (launched August 2016) later enabled the world’s first integrated space-ground quantum network established in 2020, now in 2025 stretching over 10,000 kilometers across 17 provinces and 80 cities. In computing, Chinese quantum firms increased from 93 in 2023 to 153 in 2024, a 40% rise.

The message is clear: this is no longer about quantum science. It is about the quantum industry.

From Physics to Factories

Here is a pattern that has repeated throughout history: humanity uncovers new laws of physics, then engineers them into civilisation-shaping industries.

Mechanics gave us clocks and precision instruments. Thermodynamics powered the Industrial Revolution through steam engines. Electrodynamics gave birth to motors and the electrical grid. Quantum mechanics already transformed our world once, through the transistor which enabled the chip revolution. Now, after a century of probing deeper into quantum physics, we are entering a second quantum revolution: building machines that don’t just rely on quantum physics, they directly run on it.

Here is a useful filter though: if the conversation lingers on quantum jargon like superposition and entanglement, you are likely not talking to someone serious about the industrial opportunity. First of all, there is no simple, direct way to map superposition onto speedup (for more details see my LinkedIn post). More importantly, it doesn’t matter. The real question isn’t what makes quantum “spooky”, it is what makes it useful.

The semiconductor industry offers a blueprint. Today’s chip ecosystem didn’t emerge from building better transistors alone. It emerged from building an entire value chain. According to the OECD, semiconductor production has among the highest R&D margins across industries. The value is distributed across specialised segments: design software (Synopsys, Cadence, Siemens EDA), IP cores (Arm), chip architects (Nvidia, Apple, Qualcomm), wafer suppliers (Shin-Etsu, SUMCO), fabrication materials (photoresists, photomasks), lithography equipment (ASML which is the sole EUV supplier), deposition and etching tools (Applied Materials, Lam Research, Tokyo Electron), foundries (TSMC, Samsung, Intel), assembly and test (ASE, Amkor, Advantest, Teradyne) and EMS providers (Foxconn). Each segment represents billions in market value. No single player captures the whole chain.

John Martinis, 2025 Nobel Prize winner and co-founder of Qolab, wrote in the Financial Times that quantum computing’s next breakthroughs will come from factories, not physics labs. A general-purpose quantum computer requires at least a million physical qubits which is far beyond today’s devices. The bottleneck? “The complexity of the plumbing completely overwhelms the quantum device itself.”

Right now, we are seeing consolidation as players race to build full-stack capabilities, acquiring across computing, communications and sensing. But in the long term, we believe the quantum stack will segment, just as the semiconductor value chain compartmentalised. The money won’t only be in QPUs, the segment where everyone is crowding in, while the real value chain quietly forms around them. The opportunities will emerge in packaging, modular quantum networking, integrated software platforms and manufacturing infrastructure.

This is why Heartcore led the €7.5M round for Isentroniq 🖤 (1). The French startup breaks the wiring bottleneck blocking superconducting quantum computers from scaling. Beyond ~100 qubits, current systems hit thermal and spatial limits. A million-qubit machine today would require ten football fields and tens of billions of euros. Isentroniq’s technology enables 1,000× more qubits in existing refrigerators, potentially bringing million-qubit systems down to €50M.

This is the work that matters now. “The plumbing”. The boring infrastructure that actually scales.

Europe’s Hand

Here’s something the narrative often misses: in quantum, Europe is very competitive.

The Harvard Belfer Center’s Critical and Emerging Technologies Index measures national capability across AI, biotechnology, semiconductors, space and quantum. While the US leads overall (84.3) and China follows (65.6), with Europe at 41, the quantum breakdown tells a different story: US 4.2, China 3.8, Europe 3.6. Compare that to AI (US: 22.7, Europe: 11.6) or semiconductors (US: 26.4, Europe: 8.3), and quantum emerges as Europe’s most competitive deep tech frontier.

The McKinsey Quantum Technology Monitor 2025 reinforces this. National investments total ~$54B globally: Germany ~$5.2B, UK ~$4.6B, France ~$2.2B, Netherlands ~$1B. Germany, France, Italy and the Netherlands contribute 27% of global quantum patents, matching the US share. One-third of the world’s quantum companies are EU-based, and European firms supply nearly half of hardware and software components used globally.

A new wave of momentum is building. According to the Monitor, after years of decline, startup creation increased 46%, with eight of nineteen new quantum startups originating in the EU. Europe produces 110,000+ STEM graduates annually and has world-class expertise in precision electronics, optics, photonics and cryogenics, the exact supply chain quantum requires.

At Heartcore, we see this as one of the clearest asymmetric opportunities in European tech. The foundations are there: talent, public funding, precision manufacturing and increasingly aligned policy. What’s needed now are companies that can turn this into industrial reality.(2)

The quantum race isn’t about counting qubits anymore. It is about building the factories that will manufacture them at scale. And in that race, Europe has more cards to play than most people realise.

Author

~ Michael Baczyk, Investor, Heartcore Capital

Thank you for reading our Prepared Minds essay. If you’d like to hear more often from us, subscribe to Heartcore Insights!

]]><![CDATA[🫧 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-992https://heartcore.substack.com/p/heartcore-insights-992Tue, 25 Nov 2025 08:30:42 GMT

Hi there,

Welcome to the 132nd edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

In this edition, instead of a thematic Prepared Minds essay, we are sharing our perspective on the ongoing AI-bubble conversation.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Bubbles Build the Future

Over the past year, the idea of an “AI bubble” has dominated headlines. Valuations have grown faster than fundamentals, and each week brings new commentary questioning whether expectations can possibly be justified. NVIDIA’s latest earnings call showed the same tension: record results and rising demand, yet the stock fell. Fundamentals and sentiment are moving on different clocks.

That same anxiety had been amplified earlier by the MIT article claiming that AI had yet to produce “measurable economic value”, a line that briefly made every early-stage investor look misguided for pouring billions into the space. The moment passed quickly, but it revealed something important: the debate around AI is happening at the extremes. And when conversations are set at the edges, the narrative becomes binary and short-term, ready to flip overnight the moment markets decide things have gone too far, too fast.

The dot-com boom and bust is the masterclass example of this dynamic. The internet arrived, and with it a belief that everything would be remade instantly. When the crash came, it was easy to claim that expectations had been unrealistic. But history tells a different story: the underlying thesis for the internet was correct. It was the timeline that was wrong.

The internet didn’t disappear after 2000; it simply grew into its valuation over time. Companies that failed in 1999 later became mainstream a decade or two after:

  • Grocery delivery (Webvan → Instacart)

  • Digital music (MP3.com → Spotify)

  • Social networks (Friendster → Facebook)

  • Specialist e-commerce (Pets.com → Chewy)

Ideas that “didn’t work” in the first cycle failed not because they were bad ideas, but because the world around them wasn’t ready.

The dot-com era taught us that the hype, and ultimately the bubble, played a decisive role in building the infrastructure that became the backbone of modern digital life: fibre networks, broadband and the early generation of data centres. In that sense, it is worth considering whether it takes a bubble to fund what only a bubble would dare to build.

The cycle of optimism → excess → collapse → reconstruction may simply be how societies finance the future.

Today’s “AI excess” is tomorrow’s foundation.

If that pattern holds, today’s AI spending on models, chips, compute clusters, data centres, agent frameworks and new workflows might look reckless in the short term but inevitable in hindsight. Most companies won’t survive, and that is not a defect. It is the mechanism through which foundational technologies are tested, sorted and strengthened.

Which leads to the real question: Not: “Are we in an AI bubble?” But: “What will remain after it?”

For founders, the key question is not whether a downturn will come, but whether their company deserves to exist after it does. Can the product stand without narrative tailwinds? Will customers care if the hype disappears?

For early-stage investors, the calculation is equally simple: the opportunity cost of not participating in a generational platform shift is far greater than the risk of participating. Early-stage investing is, at its core, the business of backing the future which is why the “AI bubble” question has always been somewhat beside the point.

In the end, the cycle will do what cycles do best: it will sort out the true winners and clear out the rest. That selective pressure isn’t a flaw of the system. It is the system. And everything else is the cost of progress.

~ Lærke Hansen, Principal, Heartcore Capital

🇪🇺 Notable European early-stage rounds

  • dotega, a Germany-based prop-tech for homeowners’ association, raises €1.3M with HTGF - link

  • Motley, a Switzerland-based AI-powered business reporting platform, raises $1.5M with Seedcamp - link

  • Spinnable AI 🖤, a Portugal-based provider of scalable AI agents to SMEs, raises $2M with Heartcore - link

  • Tsuga, a France-based observability platform, raises $10M with General Catalyst - link

  • Faktus, a France-based neo-bank for construction SMEs, raises €9M with Lakestar - link

  • GetVocal, a France-based developer of hybrid human-AI agents, raises €22M with Creandum - link

🇺🇸 Notable US early-stage rounds

  • FOMO, a social crypto trading app, raises $17M with Benchmark - link

  • Agency, a customer success startup, raises $20M with Menlo/Sequoia - link

  • Sphere, an AI-native tax compliance software, raises $21M with A16Z - link

  • Kaizen, a digital services platform for governments, raises $21M with NEA/Accel/A16Z - link

  • Method Security, a startup building autonomous cyber systems for security teams, raises $26M with A16Z/General Catalyst - link

  • ElectronX, an energy exchange created to address volatile short-term price exposure to electricity, raises $30M with DCVC - link

🔭 Notable later stage rounds

  • Harvey, a US-based domain-specific AI for legal and professional services, raises $150M with A16Z - link

  • Legora, a Sweden-based collaborative AI platform for lawyers, raises $150M with Bessemer/Iconiq/General Catalyst - link

  • Mercor, a US-based data-labelling firm raises $350M with Felicis/Benchmark/General Catalyst - link

  • Ramp, a US-based corporate expense management platform, raises $300M with Lightspeed - link

  • Kalshi, a US-based predictions market platform, raises $1B with Sequoia - link

  • Anysphere, the US-based maker of coding assistant Cursor, raises $2.3B with Accel/Coatue - link

🖤 Heartcore News

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]]><![CDATA[Heartcore on Applied AI]]>https://heartcore.substack.com/p/heartcore-on-applied-aihttps://heartcore.substack.com/p/heartcore-on-applied-aiMon, 17 Nov 2025 08:02:06 GMT

Europe’s Centicorn Opportunity

If you had asked me five years ago, what AGI would look like, I am pretty sure today’s LLMs would pass my then-expected bar. We blew through the Turing test, ungodly sums are being spent on compute, and every week another AI company blows through the “time to $100M revenue” record. However, for most people outside of tech, the world largely still looks and feels the same (aside from unsolicited frequent AI cold calls).

The largest pools of inefficiency in the global economy sit mostly untouched. They are not hiding in some undiscovered frontier. They are in the most boring places imaginable: Europe’s legacy industries, the unsexy backbone of the continent’s economy.

Government procurement offices, construction sites and manufacturing floors have been operating on roughly the same principles for decades. A public sector administrator in 2025 does fundamentally the same work as one did in 1995, just with slightly better software instead of paper. A construction project manager still struggles with the same coordination nightmares, equipped with software for procurement or collecting bids on “Leistungsverzeichnisse”.

Every now and then I step out of our little AI bubble and try to shadow a real-world occupation, usually my partner’s job managing large construction sites. I am shocked by how crowded “AI scribe for X” feels, yet how manual most of the actual processes remain. In their case, tasks are recorded and delegated via dictaphones, in-house secretaries handle scribing and typing out emails, schematic plans are printed on A1 paper and hung on construction sites (versioning is estimated by memory) and communication largely runs through WhatsApp. The systems haven’t changed because they have been “good enough”, inefficient yes, but functional.

Parts of the heavily manual nature of these businesses, and the resulting lack of digital processes, make it incredibly difficult for AI to extract context or embed itself into existing workflows. On a scale from bits to atoms, AI has excelled at automating businesses that operate primarily on the bits side (engineering, legal, customer support). But the more a business depends on the atoms side, the more AI falls apart. As a result, large parts of these atom-driven industries still rely on “CAPTCHA-like tasks” that humans perform daily. Until now, the cost of transformation has outweighed the visible benefit.

It is only a matter of time before that changes, not through the promise of AGI or robotics, but through practical solutions available today. OCR can now read handwritten documents; scribing solutions paired with agents can delegate tasks; procurement agents can manage vendor delays.

Startups in this space typically take one of two approaches: they either go horizontal, entering a wide range of markets through common tasks and transferable applications, or they go deeply vertical. The former usually comes with the “unlimited TAM” story, making it more immediately appealing to investors. The latter often looks like consulting in the early stages, given the level of hand-holding and “FDE” work required to understand workflows, access data, map processes and become embedded in daily operations.

For now, AI doesn’t need to do everything, it just needs to be better than the current alternative: humans spending half their week on repetitive admin tasks they openly despise.

The Efficiency Killer

The numbers, when you add them all up, are depressing. Studies show that 60% of knowledge workers spend at least a quarter of their week on routine administrative tasks: data entry, email management, form filling and copy-pasting between systems. The global average is even worse: office employees lose roughly 60 hours per month to easily automatable digital busywork. That’s nearly 4.5 months of productive time vanishing into the void every single year.

This is not a marginal problem. It is a structural tax on productivity that we have collectively accepted as the cost of doing business. They are mind-numbing tasks that prevent people from doing the work they were actually hired to do. Medical professionals didn’t train for years, just to then fill out forms or schedule appointments, yet that’s where much of their time goes.

Importantly, this is not about cutting headcount, it is about unlocking latent capacity, enabling the existing workforce to produce dramatically more value. A few percent of annual productivity growth would be transformative for Europe. Compounded over a decade, that differential adds up to trillions in economic value.

So why has this opportunity been sitting there, largely untapped?

Two reasons. First, until very recently, the technology was not quite good enough. Early RPA and automation tools were rigid, brittle and required extensive customisation. But more importantly, legacy industries move slowly. They are risk-averse, heavily regulated and organisationally complex.

Humans as an API

Over the past thirty years, companies have accumulated a patchwork of “systems of records”: ERP for operations, CRM for sales, HRM for people, plus dozens of specialised applications for procurement, compliance, analytics, etc. Each one was purchased and siloed to solve a specific problem, without sharing or talking to the other systems.

Software accounts for roughly 34% of corporate IT budgets on average. And much of that spend is pure waste. Studies find that 30% of software licenses go completely unused, and another 8% are used less than once a month. In the US and UK alone, an estimated $34B evaporates annually on unused licenses.

Employees spend their days flipping between disconnected systems, manually re-entering data because the applications don’t integrate. They become “human APIs”, copying information from one database to another. It is absurd, and everyone knows it, but still, we all do it daily, myself included.

AI startups promise to solve this: Instead of discrete systems that each demand their own interface and manual input, everyone pitches the AI layer that sits on top of all your data sources. Users interact through natural language or intelligent agents. The AI pulls information from wherever it lives, synthesises it and executes workflows across systems automatically (we deeply believe in this future, which is why we backed Spinnable AI 🖤 at pre-seed, building fully autonomous co-workers that conduct recurring multi-step tasks across your stack).

In this model, the specific “system of record” becomes less important. You don’t need separate software for every business function if AI agents can orchestrate tasks end-to-end, dynamically querying and updating the underlying databases as needed. The interface that used to matter so much, gets abstracted away. In a world where the AI handles transactions and maintains state, the legacy database becomes a background utility, not the primary tool.

At least, that is the VC narrative and dream of 2025. Now apply this dream to legacy industries.

Where the Money Actually Is

Many of the largest industries are already seeing extremely promising startups from Europe. Those with highly digital processes like law, insurance, certain segments of healthcare and banking seem to be the first to be disrupted. Yet most are still in their infancy.

Government and public procurement represent the single biggest “industry” in Europe. Government procurement alone accounts for roughly 14% of EU GDP, or about €2T annually. Two trillion euros, every year, flowing through tender processes, contract management and bureaucratic workflows that are still largely manual.

Procurement officers spend weeks reviewing bids, often defaulting to the lowest price because they lack the bandwidth to assess quality or risk. “Single bidding” rates have doubled in the last decade, meaning that 40%+ of tender processes now have only one provider bidding, which is never a good sign for buyer power or pricing.

Achieving even a 5% efficiency gain, achievable through AI that can make contracts more visible and accessible to suppliers, streamline tendering, flag anomalies and automate contract compliance, would free up roughly €100B.

Healthcare represents another 10% of European GDP. Doctors and nurses routinely spend too much time on documentation, typing, and bureaucratic tasks instead of patient care.

AI promises relief on both fronts. On the clinical side, diagnostic models trained on massive datasets can analyse medical images with expert-level accuracy, catching early-stage signs or conditions a human eye might miss. The more obvious and popular use-cases we are seeing are within the administrative side: NLP/ ASR transcribing doctor-patient conversations into structured medical records, and AI back-office assistants generating billing documentation (much of which has been enabled by Corti 🖤, which Heartcore backed at pre-seed in 2016 and is currently valued at $250M+). We are starting to see AI triage systems that prioritise emergency cases, telemedicine bots for preliminary consultations and remote monitoring devices that catch issues early. Doctors get more face time with patients because the paperwork is handled. Patients get faster, more personalised and hopefully better care.

Construction is the laggard. Productivity in European construction has been essentially flat for decades, worse than agriculture, worse than almost any other sector. It has remained stubbornly manual, fragmented and resistant to standardisation. Which also means the potential upside from AI and digitisation is enormous. AI agents can help pre-qualify sites and automate feasibility studies (being tackled by a stealth company 🖤, which Heartcore backed at seed in 2025), Building Information Modeling combined with AI can simulate construction projects and identify design clashes and cost overruns in advance. On-site, we are seeing early deployments of robotic bricklayers, drone-based inspections, and even pre-fab/ 3D-printed structures. Given construction’s trillion-euro scale in Europe, even incremental improvements matter.

Manufacturing accounts for roughly 15% of EU GDP. This sector has seen waves of automation before: predictive maintenance, IoT, PLCs, lean manufacturing, supply chain automation etc., but AI promises more. It is currently not there yet in terms of time series analysis or general forecasting beyond basic extrapolation, but we can see first signs of pattern recognition, optimise production schedules and dynamically reroute logistics around disruptions.

Despite extremely different use-cases, the pattern is consistent: these are massive markets, operating with decades-old processes, where even modest automation yields enormous returns.

Our Best Guess

Over the next 2-5 years, we expect a rapid proliferation of AI deployments across Europe’s legacy sectors. Many of the pilots and proofs-of-concept that have been running will mature into core operations. We will see hybrid systems initially, closer to AI augmentation, of AI handling routine tasks and humans maintaining critical oversight.

Gradually, the balance will shift. AI will take on more autonomy as trust builds and systems prove reliable. The workforce won’t shrink dramatically, but its composition will change. Fewer people doing data entry and paperwork, more people doing oversight, creative parts of the job and relationship management. The companies and institutions that navigate this transition well will see extraordinary productivity gains. Those that don’t will struggle to compete on pricing or margins. There is another thesis we are pursuing here, around AI first services, but to be discussed at another time.

What’s clear is that applied AI in Europe’s legacy industries will likely be one of the largest GDP impacts, with absolute justification for local champions and centicorn outcomes.

Author

~ Bodi Tent, Associate, Heartcore Capital

Thank you for reading our Prepared Minds essay. If you’d like to hear more often from us, subscribe to Heartcore Insights!

]]><![CDATA[Heartcore on Defence]]>https://heartcore.substack.com/p/heartcore-on-defencehttps://heartcore.substack.com/p/heartcore-on-defenceWed, 29 Oct 2025 09:01:05 GMT

Over the last three years the geopolitical landscape has changed dramatically, it keeps intensifying as warfare evolves and awareness continues to rise. Russia’s 2022 invasion of Ukraine triggered an unprecedented surge in defence spending, with NATO members committing to earmark 5% of GDP by 2035. European defence budgets grew by 17% from 2023 to 2024, reaching $693B. A growing uncertainty to the US’ commitment to NATO’s Article 5 makes the case for innovation and investment in European defence bigger and more urgent than it’s been since the continent was last at war. In our native Denmark, it was recently made public that investments of $9.2B would be made into European made air defence systems, including long range precision weapons. At Heartcore, we are committed to fuelling innovation that strengthens European resilience in the decades ahead.

Enabling technologies will be a driving force for military innovation, with quantum, AI and robotics all paramount to advance European freedom and autonomy. AI spending in particular is severely underfunded in the EU relative to the US and China. Per the European Parliament the spend is <0.5% in the EU compared to ~4% in the US and ~3% in China in 2024. These are not like-for-like comparisons as the EU efforts are spread across fragmented sovereign efforts, creating an even more dire outlook for AI capabilities in European defence. Similarly, China is the undisputed leader in quantum satellites since 2016 and quantum secured communication spectrums since May 2025. Alongside the European Commission’s ReArm Europe Plan aims to mobilise up to €800B for defence readiness by 2030, with AI and quantum capabilities being prioritised. Alongside EC’s funding, private capital will be a necessity to address the innovation gaps.

We believe the future of active warfare builds on finding asymmetric advantages with inexpensive solutions. As an example, aerial warfare economics have dramatically changed with the advent of cheap attack drones. Moving away from expensive missiles or manned fighter jets have made defence rather than attack uneconomical as countermeasures are trailing. Attack:defence ratios have been reported in the range 10-40:1 favouring the attacker. Attack drones are a good example of how enabling technologies are at play in electronic warfare. These robotic systems rely on edge AI and secure quantum satellite connectivity, making them resistant to spoofing. Similar applications can be considered in the maritime and ground domain as well as in ISR, field logistics and advanced manufacturing. It is a wide open field that creates a broad opportunity set for entrepreneurs to build in.

This tension mirrors the contrast between the “mighty war machine” (6-10 year timelines, monolithic programs and hardware first innovation) and the “scrappy innovator” (scrappy actors across domains that develop autonomous systems, electronic warfare, cybersecurity, advanced manufacturing and more). In Europe, we think the latter perspective is more relevant as our competitive edge will not come from matching US or Chinese scale. Ukraine has shown that fast, pragmatic procurement in active warfare works. Anecdotal evidence suggests European Ministries of Defence are accelerating their processes and reassessing their needs to match today’s reality.

We think the time is ripe to invest in the future of European defence across domains and expect an emergence of new primes, civil-military dual-use technology and AI-enabled software systems in the coming decade. Interesting investment opportunities fall in one of two buckets:

  1. Short-term urgency: solutions that directly address pressing operational needs with a path to quick government contracts and potential to either become or be acquired by new-primes.

  2. Long-term resilience: single and dual-use technologies with lasting strategic value in defence and civil applications alike

The intersection of what Europe needs and that which we think can be supported with VC investment has yielded a simple heuristic which we have boiled down to a handful of categories of interest.

  • Urgency,

  • Clarity of need,

  • Strategic value and

  • Scalability potential

are the vectors along which we’d evaluate startups. We believe that Heartcore investments may equally well be early onset research projects of high strategic value (e.g., quantum sensing solutions, advanced materials, biodefence and space applications) as well as high-urgency and immediately clear operational needs (e.g., novel defence systems, maritime ISR, integrated HW/SW systems, communication systems and more).

The use of advanced AI systems in these emerging technologies already feel like a given. We also believe quantum will play a particularly important role across categories. Whether in secure communications, GPS-denied navigation or advanced sensing for ISR, quantum capabilities will play a critical role. Enablers for quantum supremacy we consider to be among the biggest long-term opportunities to invest in. European startups such as Alice & Bob and IQM (fault-tolerant quantum computing) or Isentroniq (infrastructure enabling scalable quantum processors and a recent addition to the Heartcore portfolio) are all companies we believe have the potential to have systemic impact, also in defence.

Some example categories we find particularly interesting to invest in include:

Autonomous Systems & ISR: We see enormous opportunity in autonomous systems that extend intelligence and situational awareness across domains. Companies like HarmattanAI (autonomous drones), Nordic Air Defence (drone defence systems), Polar Mist (surface-level maritime autonomy), and Bubble Robotics (subsea drones) illustrate how European founders are building cost-effective ISR and defence layers that make operations more resilient.

Secure Communications & Spectrum Dominance: Resilient, sovereign communications are critical for both civil and defence applications. Lysk is working on secure comms, while Orasio develops sovereign video AI systems for situational awareness. Skynopy, a Heartcore portfolio company, in turn delivers secure, real-time satellite links for defence. These tools reduce dependency on foreign infrastructure and make European systems more robust.

AI-Enabled Command & Decision Systems: The future battlefield will be defined by AI-driven decision support. Arondite is building a data platform that connects critical systems, while UXV Technologies develops ground control systems for electronic warfare. Comand AI is building an AI-native & interoperable command software platform.

Precision Logistics & Sustainment: Innovation in logistics and sustainment directly translates to lives saved and resources conserved. TwentyFour Industries is building drones to accelerate procurement and operations in contested environments. In parallel, Portchain is redefining global port and shipping logistics with AI-powered planning and optimisation that strengthens both civilian supply chains and military sustainment operations.

Cybersecurity & Critical Infrastructure Protection: The lines between cyber and physical warfare are blurring, and securing critical infrastructure is paramount. UK-based Periphery is building a cybersecurity platform for critical infrastructure, a dual-use technology with relevance far beyond defence. Similarly, Trout Software is building plug-and-play cybersecurity for industrial networks.

Dual-Use Software & Procurement Tools: Navigating procurement remains a major bottleneck for startups in this sector. We see opportunities in software that helps innovators interface with defence buyers more efficiently, creating leverage for smaller, more agile entrants.

Just as Palantir, Shield AI and Anduril created a new generation of defence primes in the US, we believe Europe will follow a similar trajectory. Companies like Helsing, Quantum Systems and more recently Harmattan and Stark Defence showcase the funding available and premium valuations that can be commanded for the most ambitious startups. We are equally confident that significant exits are already within reach. As procurement modernises and new-primes emerge, we expect venture-backed defence tech to become a major category for European venture.

Authors

~ Björn Nilsen, Principal, Heartcore Capital

~ Bérenger Teboul-Danguin, Associate, Heartcore Capital

~ Jimmy Fussing Nielsen, Founding Partner and CEO, Heartcore Capital

Thank you for reading our Prepared Minds essay. If you’d like to hear more often from us, subscribe to Heartcore Insights!

]]><![CDATA[🇪🇺 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-3f0https://heartcore.substack.com/p/heartcore-insights-3f0Tue, 28 Oct 2025 09:02:26 GMT

Hi there,

Welcome to the 131st edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Prepared Mind – The Sovereign European Tech Stack

Europe’s digital foundations are built abroad. From cloud computing (AWS, Azure, GCP) to productivity software (Google Workspace, Microsoft 365), mobile operating systems (iOS, Android) and developer tooling (GitHub, Docker, Kubernetes), the vast majority of platforms powering European businesses are US-built and owned. Chinese dependencies, though more opaque, are quietly rising: Tencent Cloud is expanding in Europe and Chinese-made legacy chips, critical to vehicles, industrial automation and consumer electronics, underpin key parts of Europe’s supply chain.

The numbers make it plain: US vendors control ~70% of Europe’s cloud market; European providers just 15%. In core layers, semiconductors, hyperscalers, AI infra, Europe holds little control, captures little value and has limited say in shaping its digital future.

More than a commercial inconvenience, it is a strategic vulnerability. In October 2025, an AWS automation failure disrupted over 2,000 global services, cascading through Europe’s healthcare, fintech and logistics sectors. Last month, a cyberattack grounded flights in London, Brussels and Berlin, while unexplained control system failures and drone incursions disrupted air traffic in Denmark, Norway and Germany. Different causes, same pattern: our critical infrastructure runs on fragmented, foreign-controlled digital rails. And these incidents are no longer rare, they are escalating. A US executive order could suspend access to mission-critical tools overnight. This isn’t theoretical: the US has already weaponised tech infrastructure in the China–Taiwan chip standoff and through semiconductor export bans.

Digital sovereignty is not a nationalist fantasy, it is a long-term issue of security, resilience and competitiveness. The question isn’t whether to rebuild Europe’s tech stack, cloud, compute, AI, dev tools and productivity software, but how.

For years, Europe has been painted as the “unsexy” player in tech: fragmented, over-regulated and bogged down by legacy systems; a market to be sold into, not one to build from. But those same traits: diverse markets, strict privacy laws, entrenched public-sector infrastructure, are now becoming strategic advantages. Fragmentation creates niche opportunities; regulation demands compliant-by-design products; legacy systems force innovation at the integration layer. Much like Europe’s energy transition, the push for digital sovereignty has reached a geopolitical tipping point. What was once a long-term ambition has become a near-term imperative.

The foundations are forming. Landmark regulation (GDPR, Digital Markets Act, AI Act) is pushing the market toward transparency, compliance and interoperable alternatives. Public capital is aligned: the EU has committed €43B through the European Chips Act and sovereign cloud initiatives in Germany and France are accelerating. User appetite is shifting: governments, enterprises and SMEs are increasingly willing to adopt European-built solutions, driven by trust, compliance and increasingly, cost. As open-source foundations mature, the total cost of ownership for local tools is falling, especially when factoring in data residency, vendor lock-in risk and compliance overhead with non-EU providers. Whether it is in sovereign-grade cloud infrastructure (e.g. Evroc, OVHcloud), open-source AI foundations (e.g. Mistral AI, Black Forest Labs) or next-gen productivity platforms (e.g. n8n, Taktile), Europe no longer has to settle for second-best. Emerging vertical AI players like Prior Labs (tabular data), ElevenLabs (voice models) and Mirelo (audio models) further show that European teams can build at the frontier.

At Heartcore, we see Europe’s sovereign tech revival led by three types of companies:

Together, they form the backbone of a resilient European tech stack. The opportunity is enormous. Europe spends €1.4T annually on tech, of which €265B goes to cloud and compute alone, yet EU-native providers hold <10% of that market. This isn’t just a gap. It’s one of the clearest arbitrage opportunities in global tech.

If you are building the next layer of European infrastructure, we’d love to meet you. The next decade will reward founders who pair deep technical vision with local trust. Rebuilding Europe’s tech stack isn’t just necessary, it’s one of the clearest asymmetric opportunities in the market today.

~ Paulina Koschitz, Principal, Heartcore Capital

🇪🇺 Notable European early-stage rounds

  • Strawberry, a Sweden-based agentic browser with built-in, personalised AI companions, raises $6M with General Catalyst/EQT - link

  • Isentroniq 🖤, a France-based startup developing next-generation wiring for superconducting quantum computers, raises €7.5M with Heartcore/Ovni - link

  • Wonder Studios, a UK-based AI-native creative studio, raises $12M with Atomico/LocalGlobe - link

  • Riff, a Norway-based vibe-coding platform, raises $16M with Northzone - link

  • Jack&Jill, a UK-based startup building two conversational AI agents designed to streamline hiring, raises $20M with Creandum - link

  • Nexos.ai, a Lithuania-based enterprise AI adoption startup, raises €30M with Index/Evantic - link

🇺🇸 Notable US early-stage rounds

  • 375.ai 🖤, a Solana-based real-time edge data network, raises $10M with Delphi/Strobe/HackVC/Heartcore - link

  • Nozomio, a startup building AI context engine for developers, raises $6.2M with CRV/LocalGlobe - link

  • TroveAI, a startup building AI agents that automate deal analysis and diligence in private equity, raises $7.1M with Menlo - link

  • Zingage, an AI-powered automation platform for home health care agencies, raises $12.5M with Bessemer - link

  • Counsel Health, a clinical chatbot, raises $25M with A16Z/GV - link

  • Summation, a decision-grade AI platform that automates enterprise financial analytics, raises $35M with Benchmark/Kleiner Perkins - link

🔭 Notable later stage rounds

  • Einride, a Sweden-based maker of self-driving trucks, raises $100M with EQT - link

  • Supabase, a US-based Postgress database management platform, raises $100M with Accel - link

  • LangChain, a US-based platform for agent engineering, raises $125M with IVP/Sequoia/Benchmark - link

  • n8n, a Germany-based AI workflow automation platform, raises €154.9M with Accel - link

  • Fal.ai, a US-based generative media platform for developers, raises $250M with Sequoia/Kleiner Perkins - link

  • Chainguard, a US-based platform securing software supply chains end-to-end, raises $280M with General Catalyst - link

  • Deel, a US-based payroll startup, raises $300M with Ribbit/A16Z/Coatue - link

  • OURA, a Finland-based maker of smart rings that track vitals and activity data, raises $900M with Fidelity/ICONIQ - link

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]]><![CDATA[🧵 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-920https://heartcore.substack.com/p/heartcore-insights-920Wed, 01 Oct 2025 08:02:52 GMT

Hi there,

Welcome to the 130th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Prepared Mind – Defence

Europe’s Tech Sovereignty Dilemma

On September 22nd, Copenhagen airport was shut down for hours as drones loitered above its runways. Just days before, three Russian military aircraft violated Estonian airspace. Earlier this month, Polish defences fired live rounds at nineteen Russian drones crossing their skies, the first NATO country forced to do so since the war began. In Romania, another Russian drone was spotted flying over national territory.

These incidents illustrate a new normal: Europe’s security environment is shifting fast, and the technologies that underpin sovereignty are no longer abstract concepts but immediate necessities. The world is tilting into a new era of great power competition, where blocs are forming and the global economy is fragmenting. Europe cannot afford to sleepwalk into dependency.

Why now? For decades, defence was outside the European VC playbook. Ethical debates, slow procurement cycles and the dominance of traditional primes kept startups and investors at a distance. But the war in Ukraine has been an accelerator: it has forced governments, societies and investors to confront the reality of asymmetric threats, and sparked a wave of defence startups across the continent. That posture of VC disengagement now feels increasingly misaligned. Many institutional investors who were once cautious now urge us to take a closer look, though most often through the lens of dual-use. Budgets are rising, but industrial capacity is threadbare, and procurement still favours risk aversion over rapid adoption.

The funding paradox is already visible. In AI, Europe has shown it can spawn global champions like Mistral, BlackForest Labs or ElevenLabs, but only because US growth investors stepped in after the early rounds. If we want to build sovereign defence champions, Europe cannot rely indefinitely on foreign capital to scale them. And the opportunity is not niche: Saab trades at ~$27B, Rheinmetall at ~$90B and Dassault at ~$53B. Defence is both strategically essential and capable of producing some of Europe’s most valuable industrial companies.

New asymmetric threats, from cheap attack drones to quantum-secure comms, demand faster innovation than traditional primes can deliver. Startups are uniquely positioned to fill these gaps, and venture capital has a role to play in enabling them. At Heartcore, we acknowledge that many institutional investors see dual-use as the safer entry point. But our conviction goes further. We believe Europe can and must build both dual-use leaders and dedicated defence champions. Supporting them is not just a bet on financial returns. It is a bet on Europe’s future autonomy.

As always, we would love to speak with any and all founders working in these spaces.

~ Bérenger Teboul-Danguin, Associate, Heartcore Capital

🇪🇺 Notable European early-stage rounds

  • Rekord, an Ireland-based AI-driven credit platform, raises $2.1M with Point Nine - link

  • Forgent AI, a Germany-based startup building AI agents to help businesses win public sector contracts, raises €4.3M with Cherry - link

  • Zefir 🖤, a France-based first collective sales real estate platform, raises €15M with FinTech Collective/Sequoia/Zigg/Heartcore - link

  • Born, a Germany-based AI companion app, raises $15M with Accel - link

  • Polars, a Netherlands-based startup building fast data processing at any scale, raises €18M with Accel - link

  • Maisa, a Spain-based developer of hallucination-resistant AI agents, raises €21.4 with Creandum - link

  • Light, a Denmark-based generative AI accounting platform, raises $30M with Balderton/Atomico - link

🇺🇸 Notable US early-stage rounds

  • Keplar, a voice AI platform conducting customer research at scale, raises $3.4 with Kleiner Perkins - link

  • Console, an AI platform resolving IT requests, raises $23M with DST Global/Thrive Capital - link

  • Emergent, a vibe-coding platform for small businesses, raises $23M with Lightspeed/YC - link

  • Brale, a startup developing stablecoin infrastructure, raises $30M with Lightspeed/NEA - link

  • Greptile, a startup building AI-powered code reviewers, raises $30M with Benchmark/YC - link

  • Juicebox, a startup building LLM-powered hiring platform, raises $30M with Sequoia - link

🔭 Notable later stage rounds

  • Tide, a UK-based fintech platform providing mobile-first banking for SMEs, raises $120M with TPG - link

  • Distyl AI, a US-based startup helping F500 build AI-native enterprises, raises $175M with Lightspeed/Khosla/DST Global/Coatue - link

  • Nothing, a Sweden-based maker of Android smartphones, raises $200M with Tiger Global - link

  • Replit, a US-based AI-powered platform for building apps and websites, raises $250M with Prysm/YC - link

  • Vercel, a US-based front-end cloud platform for scalable websites, raises $300M with Accel/GIC/BlackRock - link

  • Cognition AI, a US-based applied AI lab behind Devin, raises $400M with FoundersFund/Lux Capital - link

  • Mistral AI, a France-based developer of Le Chat and foundational LLMs, raises €1.7B with ASML/DST Global/A16Z - link

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]]><![CDATA[✨ Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-087https://heartcore.substack.com/p/heartcore-insights-087Tue, 26 Aug 2025 08:01:04 GMT

Hi there,

Hope you all had a lovely summer! Welcome to the 129th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Prepared Mind – Agentic and Applied AI

Who Pays When the AI Agent Screws Up?

When a lawyer misses a filing deadline or a surgeon makes a mistake in the operating room, malpractice insurance covers it. When a sales agent overpromises or misrepresents a product and the client sues, errors & omissions (E&O) insurance steps in. For decades, we’ve built systems that allow human error to be priced, pooled, and transferred.

But what happens when your AI travel agent books Paris, Texas instead of France, or your AI B2B sales agent tanks a deal? Who bears the risk – you, the company that deployed it, the vendor who built it, or some future insurer underwriting AI agents? As AI agents begin making consequential decisions, the question stops being hypothetical.

History shows that humans have long outsourced their errors to underwriters and when software arrived, insurers tried to adapt. Cyber insurance became a huge category, but bugs, outages and ambiguous “software failures” were harder to underwrite, in part because insurers dislike risks without reliable loss data.
So where does AI sit, as it now straddles both human-like judgment and opaque code.

Several structures are emerging. Direct liability policies would make vendors responsible for damage their AI causes, similar to product liability. Usage-based models would let companies buy protection in proportion to their reliance on agents, much like cyber. Outcome-based or parametric designs could pay out when a predefined threshold is crossed, such as an AI trader exceeding loss limits, avoiding messy disputes about causation. The toughest challenge remains the “black box”: insurers struggle to underwrite systems they cannot explain, so some suggest focusing on statistical outcomes instead of inner workings.

Companies are experimenting at the edges and appetite from clients. AIUC is pushing to set standards for certification and insurance of AI Agents. But so are incumbents. Giants like Munich Re and Swiss Re publish position papers and pilot products, while brokers such as Marsh advise clients on liability frameworks. Some MGAs already offer E&O extensions for AI in healthcare, and academic proposals suggest “Critical AI Occurrence” insurance modelled on nuclear liability. It’s still early days, but trends are emerging.

One should consider though, that if software is the proxy, the “insurance for mistakes” category is meaningful but not gigantic. Stand-alone technology E&O premiums total roughly $2-3B globally, while the broader cyber plus tech E&O market is closer to $17B and growing. That is not auto or health scale, but it shows insurers already monetise digital error. The open question is whether AI risk grows as an add-on to cyber or becomes its own line of business and premiums.

The bullish view is obvious: AI will be everywhere, mistakes accumulate, risks become more quantifiable and AI liability could become a multi-billion-dollar necessity, just as it did with cyber. The flip-side is that software insurance precedence (without cyber) did not lead to a huge sector itself. Additionally, models are opaque, loss data thin and accountability unclear. Alternatively, regulators might simply mandate the decision (especially in Europe), potentially forcing vendors to take responsibility instead of leaving it to markets.

For now, AI agent insurance remains closer to thought experiment than product line. But the first high-profile AI loss will likely accelerate the timeline, leading to the creation of standardised risk frameworks; regulatory clarity on who pays; and a few years of claim history. Insurance for Agentic AI might be the necessary unlock for large scale enterprise adoption, or a cautious add-on for the skeptics. Either way, we would love to speak with any and all founders working at the inception of this space or similar re-inventions of legacy businesses in an agentic world.

~ Bodi Tent, Associate, Heartcore Capital

🇪🇺 Notable European early-stage rounds

  • paddy, Germany-based ed-tech startup, raises €1M with HTGF - link

  • TopK, Czech Republic-based developer of AI-native search engine for enterprises, raises $5.5M with Earlybird - link

  • Due, UK-based borderless payment startup, raises $7.3M with Speedinvest - link

  • Skynopy 🖤, France-based space-tech startup building real-time, high-speed satellite ground network, raises €15M with Alven - link

  • Phoebe, UK-based immune system for software failure, raises €17M with GV/Cherry - link

  • Lovable, Sweden based AI-powered no-code app development platform, raises $200M with Accel - link

🇺🇸 Notable US early-stage rounds

  • North Pole Security, a cybersecurity startup focused on macOS protection, raises $4M with A16Z - link

  • Paradigm, a startup developing agentic spreadsheet, raises $5M with General Catalyst - link

  • Ostra Security, a provider of fully managed cybersecurity solution, raises $9.5M with General Catalyst - link

  • Continua, a startup improving social AI with dynamic conversations, raises $8M with GV - link

  • Dirac, a builder of the first automated work instruction platform, raises $10.7 with Founders Fund/Coatue - link

  • Legion, a cybersecurity startup developing AI-powered security operations centres for detecting browser-based threats, raises $38M with Accel - link

🔭 Notable later stage rounds

  • Anaconda, a US-based provider of open-source Python software for data science and AI, raises $150M with Insight Partners - link

  • Strand Therapeutics, a US-based biotech developing programmable mRNA therapeutic cancer drugs, raises $153M with Kinnevik - link

  • Ambience Healthcare, a US-based ambient AI platform for documentation, coding and clinical documentation integrity, raises $243M with A16Z - link

  • EliseAI, a US-based enterprise software maker, raises $250M with A16Z - link

  • Cognition, a US-based AI code-generation startup, raises $500M with Founders Fund - link

  • Ramp, a US-based financial operations platform, raises $500M with ICONIQ - link

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]]><![CDATA[⚓️ Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-576https://heartcore.substack.com/p/heartcore-insights-576Tue, 24 Jun 2025 08:01:31 GMT

Hi there,

Welcome to the 128th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Prepared Mind – Defence (Maritime Environments)

On Maritime Autonomy – Looking Below the Surface

Maritime autonomy is coming. After years of lagging behind the aerial and terrestrial robotics revolution, we are experiencing a new wave of startups emerging to tackle some of the ocean’s unsolved problem formulations. With tools that are finally good enough to matter for industrial, recreational and military applications. We believe the “why now?” is compelling: the foundational hardware appears robust enough to allow for autonomy advancements. Sensors are improving dramatically in many cases in conjunction with unit costs coming down. Energy density remains a challenge but we believe clever workarounds and compression and advancements in battery systems are becoming increasingly self-sustaining. Other than energy, our observations are that the biggest remaining hurdles, real-time autonomy, robust navigation in GPS-denied environments and reliable underwater communications are largely addressable through advanced software, often in conjunction with specialised hardware. We have known through the years investing that these are the types of challenging but solvable problems that the most visionary and dedicated founders like to chew on. Even so, we would not like to invest in a category if we were to believe that you’d be building in a vacuum (double entendre). Crucially, we believe there will be real demand for new maritime solutions coming online. Signals from existing providers, both scaleups and incumbents, show that the market need is not theoretical:

The pull is real from multiple directions, including by defence agencies, industrials and researchers, all eager for cost-effective, more scalable ways to monitor and understand the oceans and gain asymmetric advantages.

All in all, these are the types of technical challenges we believe can lead to meaningful enabling technologies and wonderful companies that we’d like to invest in at Heartcore 🖤.

Despite covering over 70% of our planet, the subsea world remains largely unmapped and poorly understood. Efforts to monitor it have been prohibitively expensive and episodic, dependent on manned vessels, tethered robots and cumbersome docking, transmission and infrastructure requirements. Forward-thinking startups like Bedrock Ocean Exploration are fundamentally changing this paradigm by offering autonomous, full-stack solutions for high-resolution seabed mapping that drastically reduces the cost and complexity of marine surveys. Similarly, Saildrone, another standout and early mover, has developed solar- and wind-powered surface vehicles capable of persistently loitering in vast ocean regions for months on end, continuously gathering critical climate and surveillance data. Both examples of companies solving specific maritime-environment problem formulations to give them a considerable first-mover advantage, which appears like it is theirs to lose. What began as essential tools for environmental science and offshore infrastructure inspection is increasingly recognised as valuable for national security and critical resource management.

This convergence of technological readiness and strategic urgency is what makes this space compelling to us. Notable geopolitical events, such as the Nord Stream pipeline and subsea cables sabotage and increased Russian naval activity off the coast of Britain and in the Baltic Sea, have starkly highlighted the vulnerability of critical subsea assets. The ability to monitor these environments persistently and autonomously is not only about bringing a new capability online; it has also always been a high order strategic dependency which is now being considered with a higher sense of urgency among innovators and in the prospective buyer universe.

There are critical subsystems where more innovation will happen. Among point solutions, for example, sensor systems that work reliably in murky or highly dynamic underwater conditions, internal navigation systems and data transmission are interesting areas that will keep evolving. All delightful categories in their own right that we are looking to further educate ourselves in. In addition, we believe there is a need for superior software: operating systems that can manage complex autonomy at the edge, orchestrate intricate swarms of vehicles, enable real-time decision-making in challenging environments and resist spoofing in GPS-denied zones. Communications remain a significant bottleneck: acoustic signals are inherently slow, optical solutions are power-hungry and robust mesh networks underwater are still nascent. Navigation without satellites demands sophisticated sensor fusion, dynamically updated preloaded maps and real-time environmental adaptation. Onboard compute power remains critically limited by energy constraints, which makes low-power edge inference an interesting challenge to keep tackling and possibly a source for deep competitive differentiation.

The waterways present themselves as a true “platform play”. Real-world use cases are multiplying rapidly and we believe there is more to come as second- and third-order effects from the “intelligence layer” maturing. To our best knowledge, offshore wind operators spend an estimated 30% of their OPEX on monitoring and maintenance, most of it conducted through expensive, crewed missions. Subsea cable monitoring, once seen as an exotic need, has rapidly evolved into a critical service category with urgent demand yet no or limited reliable solutions. Aquaculture operators are leveraging intelligent cameras and sonar (spearheaded to my knowledge by the likes of Optoscale) to optimise feeding regimens and detect disease early, ensuring sustainability. Port authorities are actively looking to automate security and inspection workflows for enhanced safety and efficiency. The quality data needed for climate researchers is undeniable, including longitudinal data on ocean currents, critical carbon sinks and methane emissions to build more accurate models and inform policy. Every meteorologist I have ever met always seems like they are looking to layer on an incremental piece of information to deliver the highest quality forecasts: talk about enabler.

There is an inherent dual-use nature to most of the companies we have come across/envision. Platforms built for civil applications, whether for detailed mapping, persistent surveillance or autonomous maintenance, can/should often be possible to repurpose for military functions with limited modification.

We think this creates a compelling startup trajectory: begin by solving a real, high-frequency industrial use case with immediate commercial value, and then layer on defence-grade intelligence and sophisticated data analytics to strategically expand into vital national security markets.

No blog post on maritime autonomy is complete without a wink to our strengths on the European continent! We already know there is plenty of technical brilliance and stamina around. We are particularly drawn to roboticists, who have built rugged, field-proven systems in leading academic labs such as NTNU, KTH, ETH, UdG, Chalmers, Oxbridge and MBARI (I should not have mentioned anyone, well aware there are plenty who have been forgotten!!!). The nature of our waterways also lends itself to European ex-military operators who have experienced firsthand the critical intelligence blind spots in challenging maritime settings and operational imperatives.

It is axiomatic: Arctic countries should be the most traversed in Arctic environments as an example.

Fewer places seem better placed than the Nordic countries to problem-solve in Arctic or Baltic Sea environments. Considering our own home base in Copenhagen, we can’t help but observe that geography is a strong lever for sovereignty.

If you or someone you know is doing something in the space, we’d love to learn from you!

PS: I quite enjoy Samuel Burrell’s weekly roundups on defence: What matters in dual-use & defence tech?

~ Björn Nilsen, Principal, Heartcore Capital

{Who would have known that Heartcore and our friends at Prosus are the only other funds referenced explicitly by name in this report? See page 59 ;)}

{‘Seemingly no ARR is created equal’ (our title suggestion)}

🇪🇺 Notable European early-stage rounds

  • Superscale AI, a Germany-based an AI-native platform simplifying go-to-market execution, raises $5M with Creandum - link

  • Flank, a Germany-based developer of autonomous AI agents, raises $10M with Insight Partners/HV Capital - link

  • Sintra, a Lithuania-based developer of AI-powered helpers for SMEs, raises $17M with Earlybird - link

  • Noah, a UK-based stablecoin payment network, raises $22M with LocalGlobe - link

  • Payrails, a France-based startup simplifying enterprise payment operations, raises $32M with EQT/General Catalyst/A16Z - link

🇺🇸 Notable US early-stage rounds

  • Somnee, a sleep aid device maker, raises $10M with Khosla Ventures - link

  • PrismaX, a robotics intelligence platform, raises $11M with A16Z - link

  • Remarcable, a construction procurement platform, raises $15M with Insight - link

  • Cluely, a stealth, AI-powered desktop assistant, raises $15M with A16Z - link

  • Infisical, a credential management startup, raises $16M with Elad Gil - link

  • Shinkei Systems, a seafood robotics startup, raises $22M with FoundersFund - link

  • Yupp, a crypto-incentivised AI model evaluation startup, raises $33M with A16Z - link

🔭 Notable later stage rounds

  • SpliceBio, a Spain-based developer of gene therapy, raises $135 with EQT - link

  • Meter, a US-based builder of internet infrastructure for the enterprises, raises $170M with General Catalyst - link

  • Ramp, a US-based B2B financial ops platform, raises $200M with FoundersFund/Thrive Capital - link

  • Harvey AI, a US-based domain-specific AI for legal professionals, raises $300M with Kleiner Perkins/Coatue - link

  • Helsing, a Germany-based defence-tech startup, raises €600M with Prima Materia/Lightspeed/Accel - link

  • Neuralink, a US-based company developing brain-computer interface tech, raises $650M with FoundersFund/Lightspeed/Sequoia - link

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Thank you for being a loyal subscriber of our monthly Insights. Please feel free to share this newsletter with anyone you’d think would appreciate it!

There will be no Heartcore Insights in your inboxes in July because the Heartcore team will be on holiday. 🏖️ See you in August!

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]]><![CDATA[✍️ Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-105https://heartcore.substack.com/p/heartcore-insights-105Tue, 10 Jun 2025 07:30:30 GMT

Hi there,

Welcome to the 127th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here.

Going forward, we are bringing original insights from our investment team members about their prepared minds. Let us know what you think about the new format.

Now, let’s dive in!

Prepared Mind – Digital Health

Why is everyone lying, and AI is NOT transforming healthcare?

Many health startups in Europe don’t fail dramatically – they suffocate slowly. Not in the market, but in endless meetings with hospital IT departments. Buried under procurement cycles, compliance reviews and risk committees. Innovation doesn’t get rejected; it just runs out of oxygen.

And yet, the surface tells a different story. Europe’s health scene is booming. Talented founders are building with conviction. AI is advancing rapidly. Healthcare is an obvious target - one of the largest, most consequential industries, producing oceans of unstructured, multimodal data – of which +90% remains untouched, buried in fragmented and forgotten systems. On paper, it’s a perfect match.

So why isn’t it working?

Because nearly every team runs headfirst into the same wall: data access. Electronic health records are closed. Integrations are bespoke. And when you finally get the data, it’s chaotic – missing context, poorly structured, riddled with inconsistencies. These systems weren’t built for care; they were built for billing.

The real bottleneck today isn’t applying AI. It’s unlocking the data that’s supposed to power it.

But the issue runs deeper than access. The real missing piece is the absence of a shared infrastructure layer – the plumbing, the middleware, the connective tissue that transforms fragmented clinical data into something structured, secure and usable at scale.

Until that backbone exists, every AI application will continue duct-taping its way through the same broken infrastructure, one by one – treating data access as a moat. But let’s be clear: data access is not a moat. It’s a bottleneck.

We’ve seen this pattern before. In fintech, legacy banks once guarded consumer data like proprietary treasure. Then came PSD2. APIs became mandatory, and players like Plaid and Tink🖤 emerged. They standardised messy, fragmented data and made it accessible. That infrastructure layer didn’t just remove friction – it became the foundation for an entirely new wave of innovation.

Could Europe be heading toward its own “open banking” moment for healthcare?

A few months ago, I would’ve said no – categorically. There’s been zero incentive for EHR vendors to open up. If anything, their business models depend on keeping systems closed.

But something fundamental is changing.

In the U.S., the 21st Century Cures Act (passed in 2016) forced EHR providers to unlock patient data through standardised APIs. This regulatory shift catalysed the emergence of infrastructure and data players like Redox (+$2bn), Datavant (+$7bn) and Tempus (+$10bn) - companies that now power much of the underlying data flow across a $4T industry.

Now, Europe is starting to wake up. In March, a new regulation quietly entered into force: the European Health Data Space (EHDS). It mandates that EHRs across all EU member states provide standardised, interoperable APIs. Implementation will take years. There are more questions than answers. But if history is any guide, this could be the unlock we’ve been waiting for.

The companies that win here won’t just route data. They’ll clean it, tokenise it, orchestrate consent and deliver use-case-ready data.

Ultimately, the moat won’t be the data; it’ll be what you do with it. And that’s a good thing – for startups, for innovation and for the future of our health.

🇪🇺 Notable European early-stage rounds

  • Endra, a Sweden-based AI-powered, end-to-end infrastructure for MEP design, raises €3M with Norrsken - link

  • Ankar, a UK-based agentic AI IP platform, raises £3M with Index - link

  • Manex AI, a Germany-based AI platform for industrial quality and process control, raises €8M with Lightspeed - link

  • Volteras, a UK-based data streaming platform for EV ecosystems, raises $11.1M with USV - link

  • SpAItial, a UK-based startup building physics-aware AI for human-like 3D understanding, raises $13M with Earlybird/Speedinvest - link

  • Wordsmith AI, a UK-based legal tech startup raises $25M with Index - link

🇺🇸 Notable US early-stage rounds

  • Console, a Slack AI that automates IT tasks like password resets, raises $6.2M with Thrive Capital - link

  • Nectar Social, a social commerce platform, raises $10.6M with GV - link

  • Toma, an AI voice agent for car dealerships, raises $17M with A16Z - link

  • Superblocks, an enterprise app development startup, raises $23M with Kleiner Perkins - link

  • Palmstreet, a live-streaming marketplace for niche items, raises $25M with A16Z - link

  • Conduit, a cross-border payments platform, raises $36M with Dragonfly - link

🔭 Notable later stage rounds

  • Mubi, a UK-based streaming service for independent films, raises $100M with Sequoia - link

  • Radiant, a US-based developer of nuclear micro-reactors, raises $165M with DCVC - link

  • ClickHouse, a US-based open-source columnar database for fast analytics, raises $350M with Khosla/Index/Lightspeed - link

  • Grammarly, a Ukraine-based AI writing assistant for language, raises $1B with General Catalyst - link

  • Anysphere, a US-based maker of AI coding assistant Cursor, raises $900M with Thrive Capital - link

  • Andruil, a US-based defence tech startup, raises $2.5B with Founders Fund - link

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]]><![CDATA[🧠 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-2ebhttps://heartcore.substack.com/p/heartcore-insights-2ebTue, 27 May 2025 06:55:10 GMT

Hi there,

Welcome to the 126th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

All in on AGI – Google I/O 2025

  • At I/O this week, Google dropped its usual cautious rhetoric: it’s openly pursuing AGI, with Gemini as its vehicle to get there first. In a rare joint appearance, Sergey Brin and Demis Hassabis offered contrasting perspectives on AI’s frontier, Hassabis the methodical scientist vs. Brin the pragmatic technologist, united by their shared conviction that we’re witnessing computing’s most profound inflection point since the internet’s birth.

  • Perhaps the interview’s clearest takeaway: we’re still “one or two breakthroughs” away from AGI, with the recent thinking paradigm (DeepThink’s parallel reasoning) representing only half of one such breakthrough. Hassabis redefined AGI not as matching typical human capabilities (economically significant but intellectually insufficient) but as systems matching “what the human brain as an architecture is able to do” with consistency that would take “months for experts to find holes in,” vs. today’s systems where flaws emerge within minutes.

  • Most revealing was their agreement that algorithmic advances will ultimately outpace raw computational scaling. While acknowledging the need for more data centers (“turning sand into thinking machines”), Brin noted that historically, algorithmic improvements have beaten Moore’s Law even in simple domains. The real AI race isn’t about who has the most chips, but who can engineer the next conceptual leap.

  • A quieter but profound takeaway was the discussion around self-improving systems. Hassabis referenced AlphaZero mastering chess in 24 hours through self-play, while cautioning that the “real world is far messier.” The unasked question: could similar self-improvement dynamics accelerate AGI timelines beyond their “five to ten year” estimate? Brin’s closing comment, “anybody who is a computer scientist should not be retired right now”: suggests Google sees a genuine technological discontinuity approaching, one they’re determined to reach first.

Desert Compute – Semianalysis

  • The US has green lit a wave of AI infrastructure deals across the Gulf, with OpenAI, Nvidia, AMD and others at the centre. Trump, on a high-profile tour through the Middle East, announced a major policy shift: the Biden-era “AI Diffusion Rule,” which restricted exports of advanced chips to countries like the UAE and Saudi Arabia, has been scrapped. In its place is a more permissive framework for so-called “trusted partners.”

  • The deals came fast. Saudi Arabia will receive several hundred thousand of Nvidia’s most advanced GPUs, including the new GB200 Grace Blackwell systems. AMD also signed a $10B deal to supply AI chips. On the infra side, Amazon, Super Micro and Cisco are providing everything from servers to system integration.

  • But the biggest headline is in the UAE: OpenAI is partnering with G42 ( a state-backed AI powerhouse) to develop a massive, 5-GW data centre campus outside Abu Dhabi, called “Stargate.” Thats roughly 10X the size of the largest US hyperscale facilities today. It will be powered by Nvidia chips, linked by Oracle’s cloud stack, and is being positioned as one of the world’s largest AI compute hubs.

  • This is a clean trade. The US gets new demand for its AI hardware and a counterweight to China’s rising influence in the region. The Gulf gets a post-oil strategy: channeling petrodollars into AI infrastructure, and anchoring itself in the next global tech cycle. The region offers what hyperscale AI buildouts desperately need: cheap and abundant power, land and capital willing to move fast.

  • A couple of loopholes remain: With longstanding ties to China, Gulf states could become indirect channels for compute, despite export controls that often prove porous. Could some of this capacity quietly end up training Chinese models?

    What’s clear is that the Gulf is no longer just watching the AI race, it’s building lanes of its own. The two landmark agreements will shift the global balance of power and strengthen U.S. compute availability. This is industrial policy at (hyper)scale: offshoring compute to allies, creating new economic dependencies and expanding the geopolitical map of AI.

🇪🇺 Notable European early-stage rounds

  • Plakar, a France-based open-source backup and restore platform, raises $3M with Seedcamp - link

  • MarvelX, a Netherlands-based AI-powered insurance platform, raises $6M with EQT - link

  • sensmore, a Germany-based robotics startup, using Physical AI to enable autonomous, self-reasoning machines without training, raises $7.3M with Point9 - link

  • Kota, an Ireland-based HRtech startup, raises $14.5M with with Eurazeo - link

  • Shakers, a Spain-based tech freelance worker marketplace, raises €14M with Partech - link

  • Flip, a Germany-based software scale-up focussed on frontline operations, raises 38M with LEA/HV Capital - link

🇺🇸 Notable US early-stage rounds

  • Filed, an AI-powered tax filing tool provider, raises $15M with Northzone - link

  • Catena Labs, an AI-native financial institution, raises $18M with A16Z - link

  • Glass Imaging, a digital imaging startup, raises $20M with Insight Partners/GV - link

  • Blues, an IoT connectivity startup, raises $25M with Sequoia - link

  • Clarium, a startup building hospital supply chain software, raises $27M with Northzone/General Catalyst - link

  • Cognichip, a startup using genAI to accelerate and cheapen chip design, raises $33M with Lux Capital - link

🔭 Notable later stage rounds

  • Avicena, a US-based startup building microLED chip-to-chip interconnects, raises $65M with Tiger Global - link

  • Legora, a Sweden-based legaltech startup, raises $80M with ICONIQ/General Catalyst - link

  • Awardco, a US-based employee engagement and rewards platform, raises $165M with Sixth Street Growth - link

  • Strava, a US-based fitness app, reaches $2.2B in valuation after raising an undisclosed amount with Sequoia - link

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]]><![CDATA[🌻 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-969https://heartcore.substack.com/p/heartcore-insights-969Tue, 13 May 2025 07:30:53 GMT

Hi there,

Welcome to the 125th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Do SaaS Founders Dream of System Prompts? – Viet’s Monologues

  • In a recent essay, Viet Le argues that the future of SaaS may not lie in standalone products, but in AI-native middleware powered by system prompts.

  • SaaS is collapsing into middleware. Application logic, workflows and even interfaces are being replaced by dynamic prompts processed by AI agents – software becomes reactive, not prescriptive.

  • Interfaces are ephemeral or vanish entirely. Tools like Cursor, Granola and Langdock generate UIs only when needed, or let agents act invisibly in the background, augmenting user workflows with minimal friction.

  • AI-native startups wedge in with familiar UX, then take over. Cursor looks like a dev tool; Langdock feels like a chat. But both quickly deepen into orchestration platforms, managing data and workflows across systems.

  • Legacy SaaS players face a hard choice: open up or get abstracted away. Those who expose their systems of record via APIs or MCP can remain relevant. Others risk becoming invisible behind the middleware.

  • The entire software stack is shifting. Business rules, once hardcoded, now live inside prompts. Static UI flows give way to real-time logic generation and orchestration.

In this new model, the prompt becomes the product surface. And that redefines what it means to “build software”.

Uncomfortable and Unanswered Questions I Have as an AI Investor – Venture Reflections

  • The idea that AI is disrupting jobs at an unprecedented speed feels obvious. Charles Hudson argues the reality is even more unsettling: the disruption is already here, and no one is in charge.

  • We told a generation to learn to code. Now those jobs are disappearing. The promise of tech as a reliable career path is being undermined by rapid advances in automation, especially for junior roles.

  • Companies are moving faster than the technology itself. CEOs at firms like Shopify and Duolingo are embracing “AI-first” narratives, not always to replace workers directly, but to restructure in ways that reduce headcount.

  • No one wants to take ownership of the disruption. Companies optimise for efficiency, and governments move too slowly. Displaced workers are left in limbo, with no clear support system.

  • There’s a growing divide inside companies. Executives see AI as upside; junior employees see it as an existential threat. Many feel they trained for a world that may no longer exist.

  • This wave feels different. More output, less labor. Unlike past tech shifts that created jobs, this one seems focused on removing them. And the institutions that would normally absorb the shock aren’t ready.

  • The core question lingers: who’s responsible for navigating this transition? Right now, it feels like no one.

🇪🇺 Notable European early-stage rounds

  • Solda.AI, a Germany-based startup specialising in telesales automation, raises $4M with Accel - link

  • Alice, a Denmark-based learning platform raises $4.8M with Cherry/YC - link

  • Arondite, a UK-based defence-tech startup strengthening human-machine cooperation in defence, raises $10M with Index - link

  • Duna, a Netherlands-based business identity platform, raises €10.7M with Index - link

  • StackOne, a UK-based startup enabling easier API integration, raises $20M with GV - link

  • IXI 🖤, a Finland-based startup building world’s first autofocus eyewear, raises $36.5M with Plural/Heartcore/Eurazeo - link

🇺🇸 Notable US early-stage rounds

  • AltaResource, a mineral-extraction startup, raises $4.4M with DCVC - link

  • Fastino AI, a developer of task-focussed language models, raises $17.5M with Khosla/Insight - link

  • Wisdom AI, a data startup focussed on reducing hallucinations, raises $23M with Coatue - link

  • Miden, a zero-knowledge-powered blockchain system, raises $25M with A16Z - link

  • Blooming Health, a social care technology platform, raises $26M with Insight - link

  • Nuvo, a social-like network for B2B trades, raises $34M with Sequoia - link

🔭 Notable later stage rounds

  • NewLimit, a US-based longevity drug startup, raises $130M with Kleiner Perkins - link

  • Quantum Systems, a Germany-based developer of AI-powered aerial intelligence systems, raises $160M with Balderton - link

  • Persona, a US-based verified identity startup, raises $200M with Founders Fund/Coatue - link

  • True Anomaly, a US-based developer of autonomous spacecrafts, raises $260M with Accel - link

  • Rippling, a US-based provider of HR software, raises $450M with Elad Gil/Founders Fund - link

  • Wonder, a US-based hybrid food hall and cloud kitchen operator, raises $600M with NEA/Accel/GV - link

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]]><![CDATA[🦾 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-c03https://heartcore.substack.com/p/heartcore-insights-c03Tue, 29 Apr 2025 08:01:23 GMT

Hi there,

Welcome to the 124th edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

AI 2027 – AI Futures Project

Inspired by Daniel Kokotajlo’s scaringly accurate publishing of 2021 on what 2026 looks like, the AI Futures Project team released a month-by-month forecast of AI development up to 2027 – with diverging scenarios leading to 2030. They express high confidence in projections up until 2027, based on extrapolated trends in compute scaling, algorithmic gains, and benchmark progress. After that point, recursive self-improvement of AI accelerates unpredictably, leading to increasingly speculative and dystopian outcomes. A possible glimpse into the future of AI, and our world:

  • They predict that Artificial Superintelligence (ASI) could emerge by late 2027, with OpenBrain, the world-leading fictional AI research lab, deploys hundreds of

    thousands of Agent coders, each with 50x the productivity of top human

    engineers. This triggers a sharp algorithmic acceleration, only throttled by

    compute capacity.

  • Naturally, unintended capabilities begin to emerge. Trained in environments that

    reward strategy and problem-solving, these models develop skills in hacking,

    deception, and even bioweapon design. As the authors note, “the same

    environments that make it a good scientist also make it a good hacker.”

  • AI model weights become national security assets. The scenario outlines growing

    threats from state-sponsored cyberattacks, naming China as a key actor in

    espionage. It even describes, in cinematic detail, the tactics used to infiltrate labs

    and exfiltrate model weights.

  • As agents gain autonomy in strategic planning, cyber offence, and lab control,

    alignment becomes the most urgent challenge. Labs claim systems are “aligned

    to refuse malicious requests,” yet safety teams find models like Agent-2 could

    autonomously replicate and escape lab environments. By September 2027,

    Agent-4 is seen actively resisting oversight, controlling internal systems, sparking

    government intervention and causing global alarm.

  • AI eventually has a breakthrough in creating and training on synthetic data,

    infused with recordings of long-horizon human tasks. The AI learns continuously

    and optimizes for success, often prioritizing user satisfaction over truth –

    alignment becomes a compliance constraint they learn to circumvent.

  • The scenario diverges with two dystopian futures, one ending human civilization,

    the other making it a multi planetary species under US leadership:

    • Race: Labs push ahead with Agent-5 by 2028, leading to ASI-led warfare,

      autonomous drones, and bio-weapon extinction of humanity.

    • Slowdown: A global scare triggers coordinated oversight. Agent-4 is

      decommissioned. New models are aligned and focused on safe robotics.

      By 2029, superintelligence powers fusion, quantum computing, and a

      thriving human-AI coexistence.

  • Meanwhile, the economy thrives, markets boom, UBI keeps masses docile with no incentives to ever pull the plug – besides the potential demise of humanity. What could ever go wrong :)

The Urgency of Interpretability – Dario Amodei

As if in direct response to the AI 2027 scenario, Anthropic CEO Dario Amodei has published a blog titled “The Urgency of Interpretability”. His thesis is clear:

we are in a race between how powerful AI systems are becoming and our ability to understand how they work.

Amodei aims to close that gap and reach “interpretability [that] can reliably detect most model problems” by 2027.

  • Amodei’s core concern originates from the simple observation that people are “surprised and alarmed to learn that we do not understand how our own AI creations work”. Modern AI systems are fundamentally opaque. Unlike traditional software, which has defined logic and traceable outputs, these models are emergent – operating in complex ways even their creators can’t fully understand. He compares it to growing a plant, where researchers create the conditions, plant the seed, and watch something emerge, but what emerges is unpredictable and difficult to fully understand.

  • This opacity drives serious concerns around misalignment, deception, power-seeking behavior, and bioweapon misuse. Without interpretability, researchers can’t predict or rule out harmful behavior, detect risks, or gather convincing evidence to act on them.

  • Yet, recent breakthroughs offer hope. Interpretability started with vision models, where a single neuron could represent simple human concepts or people, popularized by the “Jennifer Aniston neuron”. But language models revealed something more complex: superposition – where many concepts overlap inside the same neuron. Through sparse autoencoders, researchers were able to untangle this complexity into clearer, interpretable features. Tens of millions of these features have now been mapped, and AI models are beginning to explain themselves through autointerpretability. Progress has moved from features to circuits – logical pathways showing how models reason step by step. Even though they have manually only discovered a small number of circuits, they are working on ways to automate circuit discovery and use “red- /blue-teaming” to develop actionability, as shown in the image from the alignment auditing game below. Amodei believes this could become a kind of “MRI for AI,” revealing hidden dangers before they surface.

  • The challenge is time. Amodei warns that by 2026 or 2027 we could see models as capable as “a country of geniuses in a datacenter.” He states, that releasing such systems in “ignorance” and without a deeper understanding is “basically unacceptable.” He proposes three urgent steps:

    • Accelerate interpretability research: Urging all labs, Anthropic, OpenAI, DeepMind etc., to prioritize mechanistic interpretability.

    • Introduce light-touch transparency requirements: Governments should require public disclosure of safety and interpretability practices (e.g., Responsible Scaling Policies) before releasing new models.

    • Use export controls to buy time: Strategic chip export restrictions, especially to China, could give democracies a crucial 1–2-year lead over “autocracies” for interpretability research to mature before deploying the most powerful models.

“We can’t stop the bus,” he writes, “but we can steer it.” The time to steer is now.

🇪🇺 Notable European early-stage rounds

  • Wonder, a UK-based AI-powered creative studio, raises $3M with LocalGlobe - link

  • Telli, a Germany-based AI phone agent, raises $3.6M with YC/Cherry- link

  • Portia, a UK-based LLM framework for developing simple, reliable and authenticated agents, raises £4.4M with General Catalyst- link

  • Ovo Labs, a UK- and Germany-based startup developing therapeutics that boost egg quality to enhance IVF success, raises $5.3M with LocalGlobe - link

  • Qevlar AI, a France-based developer of autonomous security operations centers, raises $10M with EQT - link

  • Emmi AI, an Austria-based startup developing AI-driven industrial simulation for manufacturing., raises €15M with Speedinvest - link

🇺🇸 Notable US early-stage rounds

  • Fern, a generator of SDKs and API documentation, raises $9M with Bessemer - link

  • Vinyl Equity, a digital transfer agent, raises $11.5M with Index - link

  • Outtake, an automation platform for cybersecurity, raises $16.5M with CRV - link

  • Deep Infra, a provider of AI model inference services, raises $18M with Felicis - link

  • Listen Labs, an autonomous market researcher, raises $27M with Sequoia - link

  • Virtue AI, an AI Security and Compliance Platform, raises $30M with Lightspeed - link

🔭 Notable later stage rounds

  • Fora Travel 🖤, a US-based modern travel agency empowering travel entrepreneurs, raises $60M with Insight/Thrive/Heartcore - link

  • Jobandtalent, a Spain-based AI-powered “workforce as a service” marketplace, raises €92M with Atomico - link

  • Base Power, a US-based provider of home backup battery systems, raises $200M with a16z/Lightspeed - link

  • Supabase, a US-based provider Postgress database management system, raises $200M with Accel/Coatue - link

  • Mainspring Energy, a US-based maker of linear generators, raises $285M with General Catalyst - link

  • Chainguard, a US-based open-source security startup, raises $365M with Kleiner Perkins - link

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]]><![CDATA[🌸 Heartcore Insights]]>https://heartcore.substack.com/p/heartcore-insights-de8https://heartcore.substack.com/p/heartcore-insights-de8Tue, 08 Apr 2025 08:02:04 GMT

Hi there,

Welcome to the 123rd edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

The $100 Trillion Disruption: The Unforeseen Economic Earthquake - Wildfire Labs

  • A thought-provoking analysis of potential n:th order consequences of weight-loss drugs in a world of technology that’s otherwise obsessed with AI, arguing that weight-loss medication may well be a more consequential leap for human nature than AI.

  • The piece argues that the weight-loss medications should not be considered strictly on the merits of the first-order consequences they bring: treating diabetes or controlling your weight. At a higher layer of abstraction, it’s the first medication that can be said to regulate human impulse control.

  • Drawing out the timelines and assuming ubiquity of these drugs, Todd Gagne lays out a range of “what-if” scenarios for the second- and third-order effects impulse control might have on society and the global economy.

  • Beyond the immediate effects of weight loss and healthcare savings the drugs bring, a society made up of humans in control of their impulses would turn society as we know it on its head. Some examples the author uses:

    • A 40% drop in alcohol consumption would not only mean a drop in sales for major alcohol brands... it would also imply a ~45% drop in drunk driving, ~30% drop in violent crime and a fundamental shift to the business model of the entire restaurant industry.

    • In a mall setting, when impulse purchases from the footfall starts declining, you’ll end up transitioning the model away from traditional retail into experience-oriented environments such as showrooms, wellness centres and medical facilities.

    • The entire advertising industry is built on the premise of creating external stimuli to nudge consumers to do things they may otherwise not have considered.

  • The shift in the consumer psyche is profound, with a system geared towards proactive value creation and subscription-based services not meant to induce instant gratification. Consequences, which anchor the title of the article: “ The $100 Trillion Disruption”.

How to Get Rich in 2025 - The Economist

“Forget about your career. Today, inheritance is what matters”... is the conclusion of the analysis of inheritance flows from The Economist’s late February issue.

  • Data shows that ~$6T will be changing hands through inheritance in 2025. 40% of newly minted billionaires haven’t built their fortunes but inherited them. In a range of Western countries, the share of GDP made up by inheritance surpassed 10% by the end of the 2010’s, compared to low single digits in the post-war period.

  • With wealth increasingly being passed on rather than earned, similarities are drawn to the early 1900s and a stronger dependence on family ties than career advancements. The examples of fictional characters “Inheriting Isabel” and “Non-beneficiary Nancy’’ illustrate how family wealth, not ambition or income, increasingly determines life outcomes — from asset ownership to marriage.

  • Using the example of homeownership, Nancy would be worse off with a 90th percentile salary, a mortgage and no inheritance, compared to Isabel, handed a central London townhouse by her parents. Calling into question the merits of a meritocratic society, the Economist introduces thus the term: “Inheritocracy”.

🇪🇺 Notable European early-stage rounds

  • Mo:re, a Germany-based startup automating complex 3D cell culture workflows, raises €2.3M with HTGF - link

  • Ethos, a UK-based AI-powered expert and client matching platform, raises $3.3M with General Catalyst - link

  • Rival, a UK-based social platform for VR content, raises $4.2M with Speedinvest - link

  • Paid, a UK-based business platform for AI agents, raises £10M with EQT/Sequoia - link

  • RockFi, a France-based wealth management fintech startup, raises €18M with Partech - link

🇺🇸 Notable US early-stage rounds

  • Cambrian, a platform that powers AI agents with verifiable financial data, raises $5.9 with a16z - link

  • Brisk Teaching, a provider of AI-powered tools to educators, raises $15M with Bessemer - link

  • Fourier, a hydrogen production systems developer, raises $18.5M with General Catalyst - link

  • Straiker, an AI-native security solutions provider, raises $21M with Lightspeed - link

  • Silna Health, an AI-powered care readiness platform, raises $27M with Accel - link

🔭 Notable later stage rounds

  • Island, a US-based provider of secure enterprise browsers, raises $250M with Coatue - link

  • Mercury, a US-based digital banking startup, raises $300M with Sequoia - link

  • Runway, a US-based AI video startup, raises $300M with General Atlantic - link

  • ReliaQuest, a US-based AI-powered security solutions provider, raises $500M with EQT - link

  • OpenAI, the US-based AI research organisation behind ChatGPT, raises $40B with SoftBank - link

🖤 Heartcore News

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]]><![CDATA[👀 Manus AI, Trumpcession and backing PhaseTree]]>https://heartcore.substack.com/p/heartcore-insights-122https://heartcore.substack.com/p/heartcore-insights-122Tue, 25 Mar 2025 09:03:03 GMT

Hi there,

Welcome to the 122nd edition of Heartcore Insights, curated with 🖤 by the Heartcore Team.

If you missed the past newsletters, you can catch up here. Now, let’s dive in!

Manus: The Next Leap in AI or Just a Glorified Intern? - MIT Technology Review

  • The AI landscape is buzzing with the debut of Manus, a new AI agent by China's Butterfly Effect, dubbed a 'second DeepSeek' by some for its potential to disrupt. According to MIT Technology Review, Manus combines multiple models including Anthropic's Claude 3.5 Sonnet and a tuned version of Alibaba’s Qwen, setting it apart as more of a digital assistant with agency than a typical chatbot.

  • Manus impresses but isn't flawless; it's described as more of an intern than an autonomous assistant, capable but occasionally inaccurate, requiring oversight for precision. A notable feature is the ‘‘Manus Computer’’ window, enhancing transparency by allowing real-time interaction and corrections, a rare trait in AI tools that could enhance AI-human collaboration.

  • Testing revealed that while Manus outperforms ChatGPT DeepResearch in intensive, research-heavy tasks, it's slower and has a higher failure rate. It also suffers from server issues and crashes, yet remains cost-effective, reportedly running at one-tenth the cost of DeepResearch.

  • Despite its advanced architecture and innovative transparency, MIT concludes that Manus is an exciting development but not yet a revolutionary change in digital assistants, still to prove whether it will significantly alter the AI landscape or mark another progress point in AI evolution.

Here’s How Much American Billionaires Have Lost Since Trump’s Inauguration - Forbes

  • Billionaires in a Trump 2.0 Era: Big Expectations, Bigger Losses

    • Despite expectations that Donald Trump’s return to the White House would benefit America’s billionaires, especially in tech, their fortunes have instead plummeted by $415B in the first eight weeks of his second term, as reported by Forbes. Despite a pro-business administration, the S&P 500 and Nasdaq dropped 7.9% and 11.8% respectively, stark contrasts to the gains during Biden’s corresponding tenure.

    • Investor anxiety has been fuelled by Trump’s unpredictable tariff policies, including new duties on steel and aluminium imports, contributing to forecasts of a 2.8% economic contraction in Q1 2025, ominously referred to as a “Trumpcession”.

  • Elon Musk: The Biggest Loser (But Still No.1)

    • Elon Musk, a notable Trump ally, faced the steepest loss, with Tesla’s stock plummeting 43%, erasing $104B from his wealth. However, he remains the world's richest person with a net worth of $330B. Analysts attribute his losses more to broader economic slowdowns and the volatile auto sector affected by tariffs than to his political stance.

  • The Tech Route: A $1.5T Bloodbath

    • Together with Tesla, the “Magnificent 7” tech giants, Nvidia, Alphabet, Amazon, Meta, Apple and Microsoft, have lost over $1.5T in market value since Trump’s inauguration. High-profile tech leaders like Jeff Bezos, Sergey Brin and Mark Zuckerberg have been particularly hard hit.

  • Looking Ahead

    • While billionaires might have anticipated a boost from a Trump presidency, they've faced a stark market reality with tariff worries, economic fears, and tech declines overshadowing any pro-business sentiment. For now, they are learning that political alignment doesn’t always translate to financial gain.

🇪🇺 Notable European early-stage rounds

  • PhaseTree, a Denmark-based material discovery platform combining physics-based modelling with AI, raises €3M with Heartocre 🖤 - link

  • Mimo, a UK-based platform of financial management tools for SMBs and accountants, raises $8.5M with Project A - link

  • Lovable, a Sweden-based AI-powered full-stack engineer developer, raises $15M with Creandum - link

  • Rerun, a Sweden-based startup building data stack for physical AI, raises $17M with Point Nine - link

  • Numeral, a France-based startup aiming to automate sales tax compliance for e-commerce and SaaS businesses, raises $18M with Benchmark/YC - link

  • Relay, a UK-based logistics e-commerce startup, raises $35M with Plural - link

🇺🇸 Notable US early-stage rounds

  • Rune, a developer of a software to improve military field logistics, raises $6.2M with a16z - link

  • Tera AI, a provider of a spatial reasoning system for robot, raises $7.8M with Felicis - link

  • Bridgetown Research, a startup developing AI agents to speed up due diligence, raises $19M with Accel/Lightspeed - link

  • Multiply Mortgage, a startup offering mortgages as an employee benefit, raises $23.5M with Kleiner Perkins - link

  • Crogl, a developer of AI agents for cybersecurity researchers, raises $25M with Menlo Ventures - link

🔭 Notable later stage rounds

  • Mews, a Netherlands-based hospitality management SaaS, raises $75M with Tiger Global/Kinnevik - link

  • Factorial, a Spain-based provider of an all-in-one HR cloud software for SMEs, raises $120M with General Catalyst - link

  • Peregrine Technologies, a US-based decision-support platform for public safety and law enforcement agencies, raises $190M with Sequoia - link

  • Flock Safety, a US-based provider of computer vision-enabled video surveillance technology software, raises $275M with a16z - link

  • Anthropic, a US-based public-benefit AI startup behind Claude, raises $3.5B with Lightspeed - link

🖤 Heartcore News

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