Olam Labs builds behavioral and multi-agent evaluations for AI labs

Olam Labs says it builds reinforcement-learning environments and training data for AI labs, evaluating how models lie, deceive, collaborate and behave in multi-agent settings. This differs from traditional evaluations focused on coding or mathematics.

The company is developing realistic scenarios involving companies communicating in Slack, with roles such as CEO and product manager, as well as diplomacy and negotiations. Olam Labs says these qualitative behaviors are harder to verify but could be more valuable if measured reliably.

Its commercial approach is to sell labs a specific capability to improve their models, supported by benchmarks and datasets. Olam Labs has published evaluations comparing models on competition, lying and collaboration, and says more are forthcoming; it also says recent demand aligns with the direction it chose for the company four months ago.