Gray Swan, an AI security company founded out of Carnegie Mellon University’s AI safety research programme, has raised $40m in a Series A funding round as it moves to bring frontier-grade security to enterprise AI deployments.
The round was co-led by Wing Venture Capital and Madrona, with additional backing from Obvious Ventures, Snowflake Ventures, Hudson River Trading, Samsung Next, and existing investor Magarac Venture Partners. The capital will be used to accelerate Gray Swan’s go-to-market operations, deepen its relationships with leading AI labs, and grow the team supporting organisations seeking to deploy AI rapidly without undermining security.
Gray Swan has positioned itself as the go-to security evaluator for the world’s most advanced AI models, having been cited in 11 recent frontier model system cards, including those published by Anthropic, OpenAI, and Meta. Its benchmarks are embedded into safety evaluation processes for these models before they are released publicly — a level of access and trust the company says no other AI security provider holds across multiple leading frontier labs simultaneously.
The business was built on the premise that every AI deployment represents an open attack surface until proven otherwise. As AI agents have moved from experimental tools into production environments — accessing enterprise data, executing workflows, and making decisions autonomously — threats such as prompt injection, jailbreaks, and data exfiltration have become operational concerns rather than theoretical ones. Tightening global regulation has further raised the cost of deploying AI without appropriate security measures in place.
Gray Swan was founded by Matt Fredrikson and Zico Kolter, two researchers who spent more than a decade studying how AI systems fail under adversarial conditions and how those failures can be prevented. As AI adoption moved from the research environment into enterprise infrastructure, the pair identified a significant gap between what their research had uncovered and what was commercially available to address it. Gray Swan was built to close that gap.
The company currently works with more than 20 customers spanning frontier labs and global enterprises, and has established a partnership with Snowflake. As part of that arrangement, Gray Swan’s runtime AI protection is natively integrated into Snowflake’s AI ecosystem, enabling enterprises to embed the company’s security capabilities directly into the platform where they build and scale AI applications.
Gray Swan’s platform is built around three core components. Cygnal provides real-time monitoring and protection, enforcing custom policies tailored to the specific risks an organisation faces, and operates continuously with low latency. Shade is an automated red-teaming agent that runs adversarial tests against AI models and agents throughout the pre-deployment process and the CI/CD pipeline, surfacing vulnerabilities before they reach production. Arena is a continuous global competition drawing more than 15,000 researchers and security professionals who attack AI models to expose weaknesses. The platform generates more than one million real-world attack trajectories, which are used to train the models underpinning both Cygnal and Shade.
Gray Swan chief scientist and co-founder Zico Kolter said, “AI applications are growing at an unprecedented rate, and at Gray Swan we want to ensure that these deployments can continue without sacrificing reliability and security. We have spent our careers conducting research into the safety of AI systems, and we are putting this into practice to ensure the companies can deploy AI with confidence.”
Gray Swan CEO and co-founder Matt Fredrikson said, “AI is moving faster than any technology we’ve seen, and security hasn’t kept pace. Our mission is to empower the world to use AI safely and securely, and this funding lets us pursue the mission on pace with the frontier. Our partnership with Snowflake is a perfect example: bringing the same security trusted by frontier labs to the platform where enterprises are already building on their data.”
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