project
Open-source Python framework for validating and correcting LLM outputs, checking generated text against rules like format, safety, and factuality.
No evidence-backed relationships are recorded.
The San Francisco company now has $50m in total funding and a research preview, Simulations, that runs anomaly detection over replayed user traffic on each pull request. It works only if you already have traffic.
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Haize Labs sold red teaming and evaluation tooling to frontier labs and large enterprises. Its engineers are now an internal research group inside a Toronto holding company that buys small-business software.
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PolicyAware 0.4.4 evaluates identity, tenant, region, arguments and risk tier before an agent's action changes state. Enforcement sits inline on every turn, and the project's own guidance is that adopters measure what that costs.
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The $15.5 billion price works out near 39 times annual recurring revenue above $400 million, and it rests on a margin claim Harvey has not quantified: that tuning Kimi K3 beats paying OpenAI per call.
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The $15.5bn valuation is 38.75 times the $400m of annual recurring revenue Harvey disclosed, and the in-house model meant to defend that price is post-trained on a Beijing lab's open weights rather than on backer OpenAI's.
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The $550mn round at $15.6bn gets the attention, but Harvey's fourth acquihire of the year bought a team whose product is testing how agents behave across a long run nobody watched. That is the part a buyer can use.
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An agent reported a bulk insert complete when zero rows had landed. The fix is not a better guardrail on the text but a mandatory re-read of the system of record before completion can be claimed.
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