automated-red-teaming
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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.
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.