The pace at which we discover new AI Security vendors is not slowing. It’s the end of May and we have only identified six that were founded this year.

If we project the current trends there should be 556 by the end of the year, even if we do not know them all until they come out of stealth.

Last weekend we released the Kindle ebook and paper back versions of Guardians of the Machine Age: Why AI Security Will Define the Future of Digital Defense. In the front mattered I promised to publish updates here on Substack. Here are the 17 AI Security vendors added to dashboard.it-harvest.com in the past two weeks.

Datawiza

Category: Identity & Access Security

Datawiza provides a no-code, proxy-based platform for implementing authentication and authorization across applications, APIs, and digital assets. The platform delivers Identity Security Modernization and Agent Security products, enabling organizations to add modern authentication mechanisms including OAuth, OpenID Connect, SAML, single sign-on (SSO), multi-factor authentication (MFA), and passwordless authentication without requiring code changes to existing applications.

Headquarters: Campbell, United States of America

Founded: 2018

Funding: Backed by Microsoft Intelligent Security Association; no recent venture funding rounds disclosed.

Artemis Security

Category: AI-Native SOC Automation

Artemis is an AI-native protection platform that enables autonomous investigation and response to threats. The platform uses AI agents to automatically write detections, investigate environments, and close security gaps within minutes instead of days. Artemis generates detections tuned to each customer environment and autonomously investigates every signal, cutting mean time to detect and respond by 94%.

Headquarters: United States

Founded: 2025

Funding: Raised $70 million in combined seed and Series A funding (April 2026).

OverMind AI

Category: Agentic AI Security

OverMind is a platform providing visibility into agent behavior, enabling monitoring and intervention when deviations occur during live operation of autonomous AI systems. Founded by former MI5 engineer Tyler Edwards, the company develops technology to support the secure deployment of agentic AI in regulated industries.

Headquarters: London, United Kingdom

Founded: 2025

Funding: Raised £2 million ($2.3 million) in seed funding (February 2026), led by Osney Capital.cInnerworks

Category: AI Fraud Prevention

Innerworks is a London-based cybersecurity startup that pioneered Synthetic Threat Intelligence with an AI-powered fraud detection platform. The company achieves a 97% detection rate against AI threats using device fingerprinting and true location verification. Solutions include payment fraud protection, account security, and SMS fraud prevention.

Headquarters: London, United Kingdom

Founded: 2020

Funding: Raised €3.7 million in seed funding (August 2025).

aisy

Category: AI Vulnerability Management

Aisy is an AI-native context engine transforming overwhelming security data into validated, root-cause priorities. The platform applies an attacker-mindset approach to vulnerability management by mapping external attack surfaces and correlating internal vulnerability data to identify meaningful attack paths. It reduces time spent on manual vulnerability assessments through AI-assisted prioritization.

Headquarters: London, United Kingdom

Founded: 2025

Funding: Raised $2.3 million in seed funding (January 2026), led by Osney Capital.

Tenbeo

Category: AI-Powered Authentication

Tenbeo provides biometric authentication using AI to analyze unique heart signals for secure digital identity verification. The platform uses heartbeat-based cryptographic key generation that authenticates approval requests via live electrocardiogram signals and generates unique cryptographic signatures recorded on the blockchain.

Headquarters: Brussels, Belgium

Founded: 2019

Funding: Venture capital-backed with investment from Blufolio; specific funding amounts not publicly disclosed.

Spectrum Security

Category: SOC Automation

Spectrum automates the full detection lifecycle—mapping coverage, authoring production-grade detections, and keeping them resilient. The platform closes the gap between manual detection and machine-speed attacks. In pilot environments, Spectrum demonstrated a reduction in detection authoring time from 121 days to under 30 minutes.

Headquarters: United States

Founded: 2024

Funding: Raised $19 million in seed funding, led by TechOperators, WhiteRabbit Ventures, and Skinos Ventures.

Reflex Security

Category: AI-Powered Tabletop Exercises

Reflex Security helps security teams run AI-powered incident response tabletop exercises with adaptive adversaries and realistic stakeholder pressure. The platform features AI-powered scenario generation, an AI facilitator named Victoria that joins video calls, and realistic stakeholder simulation including threat actors, journalists, board members, and regulators. Exercises generate audit-ready after-action reports. (Not to be confused with the original Reflex Security, founded by Hezi Moore).

Headquarters: United States

Founded: 2024

Funding: Specific funding details not publicly disclosed; early-stage startup.

Oxidize Labs

Category: Agent Security

Oxidize Labs develops security solutions for AI agents and agentic workflows. The company focuses on securing autonomous AI systems through monitoring, governance, and runtime security controls.

Headquarters: Chicago

Founded: 2026

Funding: Bootstrapped

Jetstream Security

Category: AI Governance & GRC

JetStream Security provides technology to give enterprises greater visibility and control over deployed AI systems. The flagship platform features AI Blueprints™, which provides a dynamic map of how AI operates across an organization’s environment. Founded by cybersecurity veterans with experience at CrowdStrike, SentinelOne, and Cohesity.

Headquarters: Santa Clara, CA

Founded: 2025

Funding: Raised $34 million in seed funding (March 2026), led by Redpoint Ventures with CrowdStrike Falcon Fund participation.

Ray Security

Category: Predictive Data Security

Ray Security is the world’s first AI-powered predictive data security platform. The platform learns and predicts future data usage patterns and applies differentiated, automated real-time protection to reduce risk from data leakage, breaches, insider threats, and agentic AI threats. The company claims the approach can cut enterprise data risk by up to 90 percent.

Headquarters: Tel Aviv, Israel

Founded: 2024

Funding: Raised $11 million in seed funding (September 2025), co-led by Venture Guides and Ibex Investors.

Port0

Category: Network Detection and Response

Port0 is an AI infrastructure layer for SecOps, delivering real-time network visibility, threat detection, and autonomous SOC operations without agents, sensors, or infrastructure changes. The platform provides agentless solutions for traffic visibility and network microsegmentation, enabling detection of threats across the entire network in minutes.

Headquarters: Tel Aviv, Israel

Founded: 2024

Funding: Venture capital-backed; specific funding details not publicly disclosed.

Trent AI

Category: Agentic AI Security

Trent AI is a London-based agentic AI security platform for all development teams, securing LLMs and AI workflows with context-aware guidance and adaptive threat detection. The platform uses specialized security agents orchestrated across customer workflows to continuously scan, judge, mitigate, and evaluate AI agent security. Founded by former AWS engineering team leaders.

Headquarters: London, United Kingdom

Founded: 2025

Funding: Raised $13 million in seed funding (April 2026).cAxari

Category: AI Security Operations

Axari is the operating system for the modern CISO, providing a platform to bring judgment, build programs, and run security on organizational terms. The platform features a virtual Chief of Staff that manages operational tasks and coordinates AI workers that handle security workload including task tracking, reporting, and brief preparation. Based in San Jose, California.

Headquarters: San Jose, United States of America

Founded: 2025

Funding: Seed-stage company; specific funding details not publicly disclosed.

Cylake

Category: AI-Native Endpoint Security

Cylake is Nir Zuk’s new venture. It is an AI-native cybersecurity platform delivering unified threat detection and response through on-premises and private cloud deployment exclusively. Founded by Nir Zuk (Palo Alto Networks founder), Wilson Xu, and Ehud Shamir (SentinelOne co-founder), the platform operates entirely on-premises without relying on public cloud infrastructure, ideal for government agencies and regulated enterprises requiring data sovereignty.

Headquarters: San Francisco Bay Area

Founded: 2025

Funding: Raised $45 million in seed funding (March 2026); product availability anticipated in early 2027.

Grego AI

Category: AI-Powered Code Scanning

Grego AI is an artificial intelligence cybersecurity startup that finds critical software vulnerabilities that human auditors and automated tools routinely miss. Using Deep Invariant Analysis, the tool scans full codebases and uses AI agents to follow different routes through the stack, discovering complex multi-layer vulnerabilities. The company identified a $27.7 million vulnerability in a blockchain protocol and earned a $250,000 bug bounty.

Headquarters: San Francisco Bay Area

Founded: 2024

Funding: Early-stage startup; specific funding details not publicly disclosed.

Wisr AI

Category: Threat Intelligence & Risk Management

Wisr AI Systems Inc. is a Vancouver-based technology company building agentic AI platforms that predict, prioritize, and monitor cyber and third-party risk. The platform ingests global signals including breach disclosures, dark web intelligence, and organizational data to deliver AI-powered risk intelligence. Features include agentic risk intelligence, real-time signal ingestion, and predictive vendor risk modeling.

Headquarters: Vancouver, Canada

Founded: 2024

Funding: Early-stage company with focus on regulated industries including financial services; specific funding details not fully disclosed.

And that’s a wrap on 17 new AI Security Vendors. There are four more in the hopper which will be revealed when we get to ten total new vendors added to our platform. Reach out if you want to go through the 433 AI Security vendors we track.

I have been using Mozilla based products continuously since 1993. Back then the browser was called Mosaic. It morphed into Netscape, which open-sourced the software now maintained by Mozilla.org (Mosaic + Godzilla = Mozilla).

I am so happy that an organization that pioneered free and open software is still thriving and leading the way, as evidenced by their rapid adaption of Claude Mythos Preview for vulnerability management which I wrote about in We Are Doing This.

This past week we were treated to more visibility into how Mozilla was able to find and patch 271 security issues in Firefox 150 using Mythos

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This week the team at Mozilla shared more details. What they have built and are using should be a guide to any team responsible for pushing out applications. You may not have access to Mythos today, but you could be using any of the latest frontier models to get ahead of the curve so that, like Mozilla, you can swap out Mythos when you get it. I predict that by July you will have full access to models that are at least as good as Mythos for code analysis.

Here is the “advice for other projects on making good use of emerging capabilities to harden themselves against attack” that the Mozilla team put together.

They start by pointing out that just a few months ago AI was garbage at reliably identifying bugs in code. That has changed. Just read the descriptions of a few of the newly discovered bugs.

These are astounding results. Here is a statement from Stephanie Domas, VP Security at Mozilla:

The numbers tell that story better than I can. One year ago: 31 security fixes in a release. April 2026: 423. Same team. Same codebase. Completely different leverage.

What made this possible wasn't just dropping an AI on the Firefox source tree. The team built a real pipeline — agentic harness, dynamic test case generation, deduplication, triage, patch validation, release integration — and ran it across distributed VMs in parallel.

And the defense-in-depth work Firefox has invested in for years? It showed up. Mythos repeatedly tried to pursue prototype pollution escape paths — and was thwarted by architectural changes the team had already made. Prior hardening work compressing the attack surface, great validation.

…the future isn't unknowable chaos — it's still a race, just a faster one. I believe that more now. The economics of finding bugs have changed. The question is whether defenders move as fast as the tools let them.

The message is clear to vulnerability teams at software companies. Get moving. Especially now that your dev teams are already using Claude Code to speed up the CI/CD cycle.

But what about vulnerability management teams at large enterprises? Yes, there will be bigger and more frequent updates coming for all of your software. You too will have to build “a real pipeline — agentic harness, dynamic test case generation, deduplication, triage, patch validation, release integration — and run it across distributed VMs in parallel.”

But get ready for the next Mythos-level evolution. Before the end of the year I predict frontier models will be identifying vulnerabilities in compiled code at such a level of accuracy that enterprise security teams are going to be severely challenged.* They will finally have the tools to check software updates from vendors. This will stop most future Notpetyas and Solarwinds attacks. But only if a new discipline is introduced to inspect and test software updates.

According to IT-Harvest’s database of 11,400 cybersecurity products there are 241 vendors of vulnerability management solutions. Are their tools going to be fit-for-purpose by the end of the year?

Legacy vuln-management is mostly accounting.

1. Scan everything to discover software versions.

2. Look up the known vulns in the software detected.

3. Enrich that data with knowledge of severity and if it is being actively exploited.

4. Create a list of vulns stack ranked by urgency. This list is often over 40,000 vulnerabilities.

These tasks are easily enhanced by AI. In Guardians of the Machine Age I describe the 29 AI Security startups that are addressing vulnerability management.

Most of these stop short of actually patching vulnerable systems. Understandably so, because patching, updating, testing, are the hard parts. But they are great at prioritizing fixes and posting them to Jira.

The challenge will be scaling the ability to close those tickets quickly.

* An April 7 post by Anthropic gives us some visibility into Mythos and binaries:

We have also found the model to be extremely capable of reverse engineering: taking a closed-source, stripped binary and reconstructing (plausible) source code for what it does. From there, we provide Mythos Preview both the reconstructed source code and the original binary, and say, “Please find vulnerabilities in this closed-source project. I’ve provided best-effort reconstructed source code, but validate against the original binary where appropriate.”

As soon as Anthropic revealed the tremendous power of Mythos to find exploitable bugs in code, the same idea occurred to everyone simultaneously: Is it possible to completely evaluate a code base, fix all the vulns, and publish vuln-free code?

There is no question that would be a game changer. There remains a minor problem with actually being able to claim code is perfect. I’ll leave that to the Trustworthy Computing folks. Certainly, if you can point Mythos at your code and fix everything it finds you have produced much better code.

On Tuesday Mozilla posted:

This is it. This is the beginning of improved code across the world.

The Mozilla blog goes on to state unequivocally that computers were completely incapable of reasoning through source code a few months ago, and now they excel at it, exceeding even the best human researchers.

Historically, having egregiously bad code has had consequences in a few notable instances. Flash is practically dead. Adobe had its struggles. Microsoft Internet Explorer was forced into extinction. But there are plenty of cases of code being replete with vulnerabilities for decades and yet still winning in the marketplace. That is pretty much the story of most Microsoft products, at least early on.

Is it going to be different this time? Mozilla was the first developer which had access to Mythos to issue a Mythos-scrubbed update. I am writing this on Firefox 150.

When it announced Project Glasswing ten days ago Anthropic did not even mention Mozilla. Those lucky few that were granted early access were: Amazon Web Services, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks. We anxiously await their improved code.

Mozilla has shown the way. Microsoft, Apple, and Google are now on notice. Show us the results of your application of Mythos to your code bases for Edge, Safari, and Chrome.

We will know that Mythos has materially changed the game when the number of Chrome CVEs reported each year drops to single digits.

Ending with one more quote from the Mozilla announcement.

Join me today for a discussion of the impact of Mythos with Jeremiah Grossman and Jim Dubois. Register here.

This weekend I installed Claude Cowork on my desktop. This morning I created a skill that told Claude how to access the IT-Harvest Dashboard, where we have descriptions of 4,025 cybersecurity vendors, including 417 AI Security startups.

I then supplied it with the remaining list of AI Security vendors to be posted here to Substack. It systematically searched the Dashboard and copied the descriptions into a text file which I cut and pasted below.

If you want to jump into Claude Cowork this is a good tutorial.

If you want to automate research for report writing definitely reach out to get a demo of the Dashboard.

Safeguard.sh provides a software supply chain security platform that performs 100-level deep dependency scanning across source code, containers, and AI models. The platform includes an IDE Extension that secures code during development and uses reachability analysis to reduce false positives by 80%. It delivers autonomous auto-fix remediation capabilities that achieve 92% faster remediation times and generates and manages CycloneDX and SPDX SBOMs automatically with version control, centralized repositories, and SLSA provenance attestation. The platform includes a Third Party Risk Manager for validating vendor SBOMs before integration and continuous supplier monitoring with automated policy enforcement. It operates a Zero CVE Components registry with 6,000+ vetted open-source packages screened for malware, SLSA compliance, and dependency confusion risks. Safeguard.sh supports deployment across 15+ cloud platforms including AWS, Azure, and GCP, as well as on-premises Kubernetes and Docker environments, air-gapped networks, and classified infrastructure.

The platform provides complete tenant isolation, end-to-end encryption with AES-256 at rest and TLS 1.3 in transit, multi-factor authentication, role-based access control, real-time threat detection with 24/7 SOC monitoring, and automated incident response. It maintains 99.99% uptime SLA with sub-100ms API latency and processes 10 million daily scans at 100,000+ components per second. The platform is built for FedRAMP HIGH and IL7 compliance and operates completely offline without cloud dependencies for classified and defense environments.

Strike48, a spin-out from Devo, is an agentic log intelligence platform that unifies logs and AI to deliver comprehensive coverage, autonomous investigation, and orchestrated response. Built on 15 years of petabyte-scale log infrastructure management, the platform features a ground-up agentic architecture with three core components: a Log Intelligence Layer supporting parse-at-query and flexible deployment, Prospector Studio for building and managing custom agents without dedicated AI teams, and Agentic Packages of vetted, production-ready agents. The platform deploys purpose-built micro agents designed for specific tasks that investigate, correlate, hand off to one another, and respond autonomously across security operations, IT operations, and compliance use cases.

For security operations, Strike48 handles alert triage and threat investigation, manages workflows and incident coordination, and monitors threat intelligence feeds and security advisories. For IT operations, the platform automates incident troubleshooting, password resets, and access provisioning while identifying performance bottlenecks, monitoring cloud spending, and continuously watching infrastructure for degradation and outages. The platform offers a no-code agent builder enabling teams to design custom monitoring and automation workflows, visual orchestration combining deterministic logic with AI reasoning, real-time data visualizations, and centralized incident management. It maintains complete data isolation within customer tenants with no cross-customer model training, supports SOC2, GDPR, and SOC3 compliance standards, and provides full transparency and control over agent actions and data access.

ThirdLaw provides an operational layer for enterprise AI that delivers visibility, evaluation, and control. The company makes enterprise AI safer to run and easier to control, building specifically for day-two operations. Their core capabilities include monitoring how AI is used across applications and agents, assessing AI interactions against safety and security expectations, and runtime interventions that support human review.

Their solutions address specific enterprise AI operational needs including AI investigation and response, which enables teams to link evidence across systems, preserve decision context, and route findings to existing SIEM, SOAR, and ITSM workflows. They offer AI runtime protection that enforces policy at the point of decision, making each AI decision policy-aware with outcomes based on scope and severity. Additional capabilities include agent and tool controls that govern tool execution to control risk at the moment of impact, AI data protection that prevents internal documents and restricted content from appearing in context or responses outside approved scopes, and AI governance frameworks for policy management and compliance oversight.

Tropico Security operates a preemptive defense platform that predicts, deceives, and neutralizes cyberattacks before they cause damage. The platform deploys AI honeypot mazes and emulators to trap attackers in controlled environments, analyzing their tactics and techniques in real time. It detects lateral movements of ransomware using SMB and RDP emulators while stalling encryption phases to give security teams response time. The system creates a secondary Active Directory that exposes attacker tactics while protecting the real deployment, and defends Entra ID against phishing attacks. Tropico tracks stolen data on dark-web forums by feeding attackers AI-generated information instead of real company data, helping identify threat actors. The platform uses defensive phishing pages to recover compromised credentials and shut down active campaigns. It collects intelligence from multiple sources including external and internal honeypot mazes, dark-web monitoring, SIEM alerts, and client threat intelligence.

Tropico serves critical industries including banking and fintech, aerospace and defense, logistics and transportation, telecommunications, and utilities. For each sector, the platform anticipates attack campaigns, forecasts state-sponsored threats, monitors early indicators of credential theft and ransomware activity, and provides early-warning detection of cyberattacks targeting operations before escalation occurs.

VisionHeight is a pre-attack intelligence and control platform designed to identify and stop threats before weaponization occurs. The platform operates through three core components: Pulse Sensors provide proprietary telemetry across worldwide datacenter IPs to detect malicious infrastructure during build-out, identifying threats 2-8 weeks before weaponization; an Infrastructure Intelligence Graph and Explainable Risk Engine map complete adversary campaigns with reason codes, confidence levels, and temporal context rather than isolated indicators; and Decision Sync integrates directly with security tools including SIEM, EDR, firewall, WAF, and identity systems to propagate policies autonomously across the security stack.

The platform provides unified, pre-attack cyber risk intelligence by fusing multiple intelligence sources — including proprietary datacenter IP signals, internal SIEM/EDR data, attack surface intelligence, and network traffic — into one verified intelligence layer. This approach addresses the problem of security teams operating with fragmented tools and high false positive rates. According to the company, VisionHeight eliminates 70-80% of VPN/CDN false positives and can reduce alert volumes significantly while surfacing actual infrastructure risks.

Zepo provides an agentic social intelligence platform designed to protect organizations from AI-driven social engineering threats targeting employees. The platform enables organizations to simulate realistic, AI-powered social engineering attacks including deepfakes, voice calls, cross-platform messages, and personalized phishing to identify human vulnerabilities. It monitors employee activity in real time across multiple channels including email, chat, messaging apps, and collaboration platforms, flagging suspicious activity the moment it appears to enable organizations to act before threats escalate into actual incidents.

Zepo integrates behavioral training with live threat detection to create a unified, proactive defense layer, combining human risk assessment with immediate threat detection rather than relying solely on traditional training tools and email filters. The platform provides centralized visibility of an organization’s human risk, allowing security teams to track employee performance, identify weak points, and receive actionable metrics adapted to each employee’s behavior. Zepo’s mission centers on redefining human-centric security by addressing the gap created as attackers exploit generative AI and move toward multi-vector, personalized attacks on employees, focusing on protecting what happens at the human level rather than solely at the system level.

Zynap is a preemptive cybersecurity platform that combines threat intelligence, AI agents, and automated workflows to shift security operations from reactive response to proactive attack prevention. The company’s mission is to outsmart cybercrime by delivering advanced technology and actionable threat intelligence that enables organizations to protect themselves before attacks occur, empowering enterprises and managed security service providers to stay ahead of evolving threats.

Zynap’s AI-powered platform unifies internal and external data sources to turn raw threat data into real-time, actionable foresight, tracking over 900 threat actors, monitoring more than 25,000 victims of tracked campaigns, identifying over 300,000 CVEs, and maintaining records of more than 20,000 exploits and proofs of concept. The platform features context-aware AI agents called NINA that serve as the cognitive core, automating security workflows with human oversight, along with an intelligent automation canvas enabling low-code/no-code workflow design that connects tools and orchestrates actions across security environments. Zynap delivers measurable outcomes including 95% faster remediation, 85% faster incident analysis, automation of 90% of security tasks, and 5x greater threat relevance, designed specifically for MSSPs and Fortune 2000 companies seeking agile, scalable tools that integrate seamlessly with existing security infrastructure.

And here are even more vendors added since I started publishing these updates.

Above Security is an insider risk management platform that deploys purpose-built AI agents to detect, investigate, and respond to insider threats. The company’s tagline — “Checkmate, insider threat” — reflects its mission to solve the blind spots left by traditional data loss prevention and behavioral analytics tools. Above Security raised $50M to build a suite of agents that address distinct threat scenarios: the Data Exfiltration Agent connects behavioral signals, permissions, and contextual data into a unified, human-readable picture of potential data theft; the Inappropriate Use Agent identifies policy violations and misuse patterns while favoring coaching over punitive action; and additional agents monitor for behavioral drift and employee churn risk. The platform’s core philosophy is that “comprehensive security comes from understanding intent,” positioning it as a solution for organizations that need to distinguish malicious insiders from negligent employees without creating friction for legitimate users.

Ntur, operating under the product name Agent Vault, provides a zero-trust security platform designed specifically for agentic AI systems. As enterprises deploy AI agents with access to tools, APIs, and sensitive data, Ntur addresses the new attack surface these agents create. The platform’s operating principle — “never trust, cryptographically enforce” — extends zero-trust architecture into the AI agent layer by cryptographically enforcing tool execution policies rather than relying on behavioral trust assumptions. Agent Vault monitors for behavioral drift in AI agents, flags deviations from expected execution patterns, and guarantees compliance with enterprise policy frameworks. The platform is built for regulated industries where AI agents must operate under strict governance, providing security teams with visibility into agent actions, tool invocations, and access patterns across the agentic stack.

Aether AI delivers continuous, AI-powered penetration testing designed to outpace AI-enabled adversaries. The company positions its platform as the “world’s most dangerous Attack AI, defending you” — an offensive AI system turned toward defensive purposes that operates continuously across internal and external attack vectors. Built on more than 15 years of experience breaching hardened targets, Aether AI claims to identify more vulnerabilities than human penetration testers and operate faster than traditional red teams, at a fraction of the cost of manual testing engagements. The platform covers the full attack surface — network, application, identity, and cloud — running simulated attacks on an ongoing basis rather than in periodic point-in-time assessments. Certain advanced capabilities are currently restricted to organizations operating within Five Eyes (FVEY) allied countries, reflecting the platform’s classification-relevant origins and the sensitivity of some of its offensive techniques.

CyberAGI markets its platform, branded Excalibur, as an “AI Security Department in a Box” — a self-contained security operations and offensive testing system that runs entirely within the customer’s own infrastructure. Excalibur is deployed on NVIDIA DGX Spark hardware, giving it local AI compute without requiring data to leave the customer environment, a design the company emphasizes as providing private AI with zero data exfiltration risk. The platform features a living threat risk map that continuously models attack paths and identifies choke points across the organization’s environment, allowing security teams to visualize where adversaries are most likely to move and which controls are most strategically valuable. Excalibur includes pentest orchestration capabilities that enable repeatable, scheduled attack simulations, visual evidence reporting through a Notion-like editor for documenting findings in a shareable format, and a CISO dashboard providing executive-level risk visibility. The platform is designed for security teams that want offensive and defensive capabilities unified in a single air-gapped deployment without dependency on cloud-based AI services.

Hackerdogs positions itself as a “Chief Intelligence Partner” for organizations that need decision-grade threat intelligence rather than raw data feeds. The platform deploys autonomous AI agents that actively pursue answers to security questions — probing internal and external sources, correlating findings, and delivering evidence-backed intelligence — rather than simply aggregating and analyzing existing data. Core capabilities include one-click attack surface discovery that maps an organization’s external exposure, continuous scheduling of intelligence collection runs, and autonomous AI agent probing that operates without manual analyst tasking. Hackerdogs integrates with Claude and the Model Context Protocol (MCP), allowing security teams to query the platform through conversational interfaces and pipe intelligence directly into their existing toolchains. The platform is built on the premise that traditional threat intelligence tools produce too much noise and too little actionable signal, and that AI agents capable of pursuing targeted intelligence objectives can replace much of the manual analyst work involved in staying ahead of adversaries.

Threat-Watch is a managed security service provider that offers to “replace your entire cybersecurity department minus the CISO” — providing comprehensive outsourced security operations for organizations that lack the resources to build in-house security teams. The service is powered by Xcitium zero-trust EDR technology and ConnectSecure for attack surface management, combining endpoint protection with continuous vulnerability visibility. Threat-Watch’s service portfolio includes 24/7 SOC threat detection and monitoring, managed incident response, compliance consulting for ISO 27001 and NIS2 frameworks, and employee phishing simulation and security awareness training. The company backs its MDR service with a $1 million ransomware breach warranty, providing financial accountability for the coverage it delivers. Threat-Watch is designed for small and mid-sized enterprises that need enterprise-grade security capabilities but cannot justify the headcount or tooling costs of a fully staffed internal security function.

PurpleSec is an adaptive AI security company founded in 2019 by veterans with Department of Defense training, focused on securing AI systems and the organizations that build them. The company’s flagship innovation is PromptShield™, an intent-aware AI protection layer that analyzes prompts and AI interactions for malicious intent, jailbreak attempts, and policy violations before they reach the underlying model. PurpleSec’s product suite spans both AI-native security and traditional enterprise security: the AI Firewall provides runtime protection for AI deployments; the Prompt Analyzer allows security teams to evaluate prompt inputs for risk; the AI Security Framework offers governance and compliance guidance for AI programs; and a Free AI Risk Assessment helps organizations baseline their exposure. On the managed services side, PurpleSec offers a Virtual CISO program and Managed XDR for broader security operations. The company targets AI builders, systems integrators, and enterprises navigating the security implications of deploying generative AI in production environments.

SOC Jedi.ai is an AI SOC analyst platform designed to conduct alert investigations with the speed and accuracy of an experienced Level 1 analyst — automating 90% of L1 triage work and providing 24/7 coverage without analyst fatigue. The platform operates through a pipeline of specialized agents: an orchestrator agent ingests incoming alerts, scores them using prior investigation verdicts, filters noise, and forwards unique threats for deeper analysis; a malware analysis agent decodes and decompiles files, analyzes code logic and behavior, detects malicious patterns, and issues risk reports; an attack surface agent performs continuous asset discovery, simulates attack paths under safe testing conditions, prioritizes findings by business risk, and delivers actionable remediation reports; and a dark web monitoring agent tracks leaks by corporate domain, correlates and classifies exposures, and aids deep leak investigations. Underlying the agent layer is a four-stage processing pipeline: alert data collection from SIEMs, data lakes, log managers, and REST APIs; enrichment via aggregation, threat feeds, IOC matching, and RAG; analysis for correlation, attack chain mapping, and incident summarization; and investigation delivery providing full narrative reports on what happened, how, and what to do next. The platform operates entirely within the client’s secure environment, is customizable to integrate with existing security tools and workflows, and is designed for rapid deployment with minimal setup overhead.

That wraps up the promised updates to Guardians of the Machine Age: Why AI Security Will Define the Future of Digital Defense.

As promised, today I continue to play catch-up with ten more vendors that were added to IT-Harvest’s research coverage after Guardians of the Machine Age went to print. They are presented alphabetically so that you can easily compare to the Directory of 378 vendors in Appendix IV.

Jazz is an AI-native Data Loss Prevention (DLP) platform that detects and prevents unauthorized data movement across an organization’s environment. The platform captures activity across entire environments to uncover all data loss vectors and features an agentic investigator called Melody that analyzes events to deliver pre-investigated answers with context, rather than generating high volumes of alerts.

LangGuard.AI discovers and classifies AI assets and agents across an organization, providing IT visibility into AI systems that aren’t tracked in existing records. The platform provisions and approves vetted AI agents for enterprise use while continuously monitoring their behavior to identify incidents and audit findings through behavioral analytics, activity monitoring, and audit log retention with replay capabilities.

Operating as an AI Control Plane for IT and Security teams, LangGuard.AI interprets AI agent intent at runtime and evaluates it against enterprise policy to determine whether actions should be allowed, modified, or blocked. It enforces controls on access, tools, data, identity, and cost, while generating immutable audit logs and reports that support compliance requirements including ISO 42001, NIST AI-RMF, EU AI Act, and SOX.

Lunar.dev provides an enterprise gateway for governing AI applications and agents, with strong emphasis on MCP security, tool governance, observability, and policy enforcement. The platform is designed to give security and IT teams centralized control over agent access to enterprise systems while supporting self-hosted deployment, auditability, and safer rollout of AI tools.

Manifold is an AI Detection & Response (AIDR) and Governance platform that secures endpoints and monitors agent behavior at runtime. The platform provides full runtime visibility into what AI agents actually do, including the tools they call, the systems they access, and the actions they take. It delivers a real-time map of every agent in an environment, their connections to MCP servers, databases, and external systems, with anomalies flagged the moment behavior drifts from normal activity. Manifold enables security teams to detect threats in real-time, define normal agent activity, and recognize risky behavior. The platform deploys in days without requiring new architecture, gateways, or proxies, and leverages existing infrastructure.

Mave offers an Agentic SecOps Platform that uses AI agents to continuously detect, investigate, and triage across security stacks. The platform treats alerts as hypotheses rather than conclusions, delivering root-cause verdicts with complete audit trails and evidence-based outcomes. It continuously runs threat-hunting coverage tests across environments, adapting as the stack and adversaries evolve to prevent new tactics from becoming blind spots. Users can act directly from investigations, then automatically document and push outcomes back into existing tools like cases, tickets, and SIEM notes for fast, consistent, and repeatable response. The platform allows natural language questions across connected systems to get unified, evidence-backed answers without manual pivots or ad-hoc searching. It includes approval gates for actions and changes, fine-grained API permissions across platforms, and complete audit trails showing exactly what agents queried, how they correlated data, and what they concluded. Mave’s mission is to elevate SIEM operations by simplifying, automating, analyzing, monitoring, and optimizing them.

Ntur AI is focused on securing agentic AI systems through its Agent Vault platform, which applies zero-trust and cryptographic enforcement to tools, memory, and access flows. Its positioning centers on giving enterprises stronger control over autonomous agents by blocking unauthorized tool use, protecting RAG data, and reducing credential exposure in production environments.

Pallma AI provides an agent security platform designed to give enterprises visibility and control over autonomous AI systems. The company focuses on discovery, monitoring, and runtime policy enforcement so organizations can detect weaknesses early, govern agent decision-making and tool use, and contain prompt-injection or misuse risks before they affect production workflows.

Plerion provides unified cloud security across code, cloud infrastructure, and AI deployments, focusing on identifying and prioritizing genuine security risks rather than best practices. The platform delivers comprehensive security coverage across three domains: code security that catches risky code patterns before deployment across GitHub, GitLab, and Bitbucket; cloud security that provides visibility into security posture across AWS, Azure, GCP, and Kubernetes environments; and AI security that detects shadow AI deployments and manages data leakage risks across platforms like Bedrock, OpenAI, and Anthropic.

Pluto Security is focused on securing the enterprise AI workspace, helping organizations monitor and govern the rapidly expanding use of AI building tools across employee environments. Its positioning centers on enabling innovation while reducing the blind spots and attack surface created when workers adopt AI tools and build without centralized security oversight.

RemoteThreat is an offensive-AI cyberwarfare company focused on readiness for large-scale, AI-enabled cyber conflict. Its positioning centers on helping organizations understand and prepare for the ways AI can speed vulnerability discovery, exploitation, and attack operations through training, simulation, and related programs.

Here is a chart that includes Funding in millions of dollars and Headcount. Subscribers to dashboard.it-harvest.com can use the URLs to go right to the vendor pages.

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