End-to-end AI security and governance platform to discover, monitor, red-team and prove enterprise AI
EU AI ActNIST AI RMFISO/IEC 42001
Haize Labs
Adversarial testing and red teaming to make AI systems reliable and safe
What Haize Labs does
Haize Labs is an AI research lab and red teaming company that develops adversarial testing tools and methodologies for evaluating the safety and reliability of AI models. Founded in 2023 in New York by Leonard Tang and Steve Li, the company automates the discovery of failure modes in language models and generative AI, using techniques it calls haizing to surface harmful, unsafe, or unreliable behaviors at scale before systems reach production. Haize positions its work around deploying highly reliable AI, giving model developers and enterprises rigorous, evidence-backed evaluations of where systems break under adversarial pressure. Rather than relying solely on manual red teams, Haize emphasizes automated, algorithmic stress testing that can generate large volumes of targeted attacks across modalities and safety categories. The company has secured multimillion-dollar engagements with frontier AI organizations including Anthropic, Scale AI, and AI21, signaling that its evaluations are trusted by sophisticated model builders. Backed by $12.5M in seed funding from General Catalyst, Pear VC, and Soma Capital, Haize's distinguishing edge is its research-lab pedigree and focus on rigorous, automated adversarial evaluation for frontier and enterprise AI.
Key capabilities
- Automated adversarial red teaming
- AI safety and reliability evaluation
- Failure-mode discovery
- Multimodal attack generation
- Model benchmarking
Best for
Frontier model builders and enterprises needing rigorous automated adversarial evaluation of AI systems
Limitations
Research-lab orientation; less focused on runtime protection, governance, or compliance reporting than platform vendors.
Framework coverage
Haize Labs does not publish explicit mappings to the major AI governance frameworks. That is common for tools in the red-teaming & ai security category, where the value is technical rather than documentary — but it means you will be responsible for evidencing how it satisfies your obligations.
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AI Governance Tool Selection Kit
A vendor-comparison worksheet plus EU AI Act, NIST AI RMF and ISO/IEC 42001 requirement checklists — so you can shortlist tools against the obligations that actually apply to you.
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