Olam Labs

Founded by Om Buddhdev

Evaluate AI models in complex multi-agent simulations

Pricing model

Demo

Rating

★ People love it

Time to value

Requires Expertise

You can use Olam Labs to evaluate and train frontier AI models inside complex multi-agent simulated environments. The service measures social reasoning, cooperation, deception, and negotiation across multiple models interacting simultaneously in real time. Researchers can design custom environments with specific incentives, run benchmark arenas like social diplomacy games, and monitor emergent behaviors. By testing models under realistic multi-agent conditions, you can assess safety risks and agent capabilities before deployment, gaining detailed performance ratings across leading models in shared interactive tasks.

What Olam Labs does

Simulate multi-agent negotiation scenariosBenchmark model performance against competing modelsTrack emergent model behaviors during social interactionsAssess pre-deployment safety risks in simulated environmentsDesign custom incentive structures for AI agentsMeasure model theory of mind and deceptive capabilitiesMulti-agent simulation environments for testing frontier AI modelsSocial reasoning and diplomacy benchmark metricsCompetitive arena leaderboards measuring relative model ratingsBehavioral evaluations tracking deception, negotiation, and cooperationCustom incentive configuration for complex agent interactionsPre-deployment safety assessments based on emergent model dynamics