OPTIMA LETS AI USERS TEST MODELS ON THEIR OWN DATA

Optima addresses a critical gap in AI evaluation: most benchmarks use generic datasets that don't reflect real-world performance. The platform allows organizations to build benchmarks from their actual data and operational workflows. Beyond quality metrics, Optima measures cost and time per task—particularly valuable for agent-based applications where these factors often matter more than raw token pricing. Users gain insight into how different models perform under conditions matching their specific use cases. This approach shifts evaluation from theoretical performance on standardized tests to practical results in production environments. For teams selecting between AI models, testing against proprietary data reveals actual trade-offs in speed, cost, and output quality rather than relying on headline benchmark scores. The platform targets enterprises and developers building AI agents, where performance variations can significantly impact operational efficiency and costs.