

Enterprises need AI they can trust, control and customize. Open models give teams the visibility and ownership to evaluate AI against their standards, specialize AI with domain knowledge, and improve accuracy and efficiency.
Harvey
422 posts

@harvey
AI for the world’s most complex legal work.


Enterprises need AI they can trust, control and customize. Open models give teams the visibility and ownership to evaluate AI against their standards, specialize AI with domain knowledge, and improve accuracy and efficiency.

Last week we held Harvey Hacks, our internal hackathon. 27 projects total across our 200-person eng team. Wanted to highlight a few hackathon projects:





Come help us scale @harvey’s model training team. If you’re interested in bringing frontier agent research into the Harvey product and working with: - @baseten to scale up RL to 80M+ token virtual datarooms - @PrimeIntellect to create structured agent training environments from unstructured legal data - @FireworksAI_HQ to navigate the quality <> cost Pareto frontier with inference-time routing and advisor models - @LangChain & LangChain Labs to build efficient verifiers and close the observability <> training feedback loop - @appliedcompute to post-train open weight models and high-volume agents for end-to-end legal tasks - @EngramLab to create an entire synthetic law firm and firm knowledge memory systems for better / more efficient open-world search - @trajectorylabs & @NVIDIAAI to shape the frontier of continual learning and sovereign AI for high-stakes domains - @mercor_ai & @SnorkelAI to build out Legal Agent Bench and other benchmarks across legal and other verticals and other projects like this, then this is the role for you. Apply here: harvey.ai/company/career…









Grok 4.5 is #1 on Harvey's Legal Agent Benchmark