adversarial-testing
(5)
Klaimee
Klaimee is a San Francisco insurtech startup (YC Spring 2026 / P26) building the first liability insurance for autonomous AI agents. It stress-tests an agent, scores it across eight risk dimensions, issues a certification and financial guarantee, then attaches AI-specific liability coverage - the paperwork enterprise procurement and legal need before they will let a vendor's agent touch their systems. It covers the gap that traditional cyber and E&O policies explicitly carve out.
Straiker
Straiker is a Sunnyvale-based agentic AI security company that helps enterprises deploy AI agents without handing attackers the keys. Its platform spans three jobs - Discover AI maps the agents, MCP servers, and workflows running across a company; Ascend AI red-teams them before deployment to surface prompt injection, goal hijacking, and tool misuse; and Defend AI blocks identity abuse, memory poisoning, and data exfiltration at runtime. Founded by former Palo Alto Networks and Akamai security leaders, Straiker raised a $64M Series A in June 2026, bringing total funding to $85M.
Haize Labs
Haize Labs is a New York-based AI safety and reliability startup that automates the red-teaming, stress-testing, and evaluation of large language models. Founded in 2024 by a trio of Harvard-trained researchers, the company builds algorithms that hunt for the inputs that make AI models misbehave - jailbreaks, failure modes, and edge cases - so they can be fixed before real users find them. Its 'haizing suite' and multi-turn attack engine Cascade are used by frontier model labs including OpenAI and Anthropic, alongside enterprises like Deloitte and MongoDB.
Pareto.AI
Pareto.AI is a San Francisco-based, talent-first human data platform that connects AI labs with a deeply vetted network of expert labelers to produce premium training data, RLHF, and evaluation signals. Founded by Thiel Fellow Phoebe Yao, the company started as a bootcamp for women and work-from-home mothers, pivoted into AI data labeling in 2023, and now positions itself as the 'verification layer' for reinforcement learning on real-world expertise, turning specialist judgment into durable reward signals under the banner 'Expert data for AGI.'
Leonard Tang
Leonard Tang is the co-founder and CEO of Haize Labs, a New York AI safety startup that stress-tests frontier language models by automatically jailbreaking them before they reach the public. A Harvard math and computer science graduate who turned down a Stanford PhD, Tang built Haize into a venture that frontier labs like OpenAI and Anthropic pay to break their models on purpose. By 2024 the company had raised a $12.5M seed led by General Catalyst at a $100M valuation, roughly eight months after founding, and Tang landed on Forbes' 2025 30 Under 30 list for AI.