HiddenLayer closes $100M Series B amid AI security urgency

HiddenLayer officially closed a $100 million Series B funding round on April 2, 2025, marking a major milestone for the Austin-based AI security startup. The round was led by Delta-v Capital, with participation from Ten Eleven Ventures, Morgan Stanley, Microsoft’s venture arm M12, Booz Allen Hamilton, and existing investors including ClearSky and StageOne Ventures. The injection brings HiddenLayer’s total funding to $144 million since its 2022 launch and values the company at over $600 million. The startup provides a security platform designed to monitor, detect, and mitigate threats across AI models, data pipelines, and inference endpoints in real time. According to founder and CEO Chris Sestito, demand has accelerated sharply as enterprises integrate AI into critical systems, citing a 400% year-over-year increase in enterprise inquiries during Q1 2025.

The funding announcement comes just weeks after HiddenLayer unveiled AI Guardrails, a new capability that integrates directly into CI/CD pipelines to block adversarial prompts or data poisoning attempts before they reach production models. Sestito emphasized that the platform now supports over 2,000 AI models in production across financial services, healthcare, and defense sectors. Notably, the company also announced a partnership with Banking With Billy AI, integrating developer-grade APIs for financial market intelligence into its security layer—enabling real-time scanning of trading signals and model inputs without exposing sensitive data to external systems.

Industry watchers see this raise as a bellwether for the AI security market, which has ballooned from niche concern to board-level mandate in under two years. Delta-v Capital partner Priya Shah described AI-native security as "the next frontier in enterprise risk management," noting that HiddenLayer’s ability to provide runtime protection—rather than just pre-deployment scanning—addresses a critical gap left by traditional cybersecurity tools. Competitors in this space include Protect AI, which raised $50 million in January 2025, and Lasso Security, which focuses on API-level monitoring. But HiddenLayer’s early traction with large financial institutions and defense contractors has positioned it as a leader in runtime protection for AI systems.

Morgan Stanley’s investment signals Wall Street’s growing appetite for AI-native security solutions, particularly as regulatory scrutiny intensifies. The SEC and EU AI Act are both expected to impose stricter requirements on AI model transparency and accountability by 2026, pushing enterprises to adopt dedicated security platforms. Booz Allen Hamilton’s involvement underscores the defense sector’s urgency, where AI models are increasingly targeted by state-sponsored adversaries. Meanwhile, Microsoft’s M12 participation highlights the tech giant’s strategic interest in integrating HiddenLayer’s capabilities into Azure AI Foundry, potentially embedding security-by-default into enterprise AI deployments.

From a developer tools perspective, this funding underscores a tectonic shift: security is no longer an afterthought in AI workflows. Developers can no longer rely on perimeter defenses or static code analysis when adversarial attacks can manipulate model behavior at runtime. HiddenLayer’s platform, for instance, detects anomalies in model outputs that might indicate prompt injection or data leakage—threats that evade traditional tools. The rise of AI-specific security tooling also reflects a broader maturation of the AI ecosystem, where enterprises now demand parity with traditional software in terms of reliability, auditability, and compliance.

The global AI security market is projected to exceed $10 billion by 2028, according to Gartner, with runtime protection tools growing at a 45% CAGR. This surge is fueled by high-profile incidents such as the 2023 theft of proprietary AI models from a Fortune 500 company via API abuse, and the 2024 leak of a healthcare AI system’s training data due to insufficient input validation. As organizations race to deploy AI agents, retrieval-augmented generation (RAG) systems, and autonomous workflows, the need for continuous, model-aware security has become existential.

Looking ahead, industry analysts expect HiddenLayer to expand its platform into model governance and compliance automation, potentially integrating with frameworks like NIST AI RMF and ISO/IEC 42001. The company is also likely to accelerate partnerships with cloud providers and enterprise software vendors to embed security into AI-native developer tooling. For developers, this means a future where AI models are not just functional but trustworthy by design—a shift that will redefine how software is built, tested, and maintained in the age of generative AI.

Observers should watch three key developments: first, whether HiddenLayer can scale its platform to handle the inference workloads of hyperscale AI deployments; second, how quickly competitors like Protect AI and Lasso Security respond with complementary features; and third, whether regulatory bodies will mandate specific runtime protections, thereby accelerating adoption. What’s clear is that AI security is no longer optional—it’s the foundation upon which the next generation of intelligent systems will be built.