video1.0<iframe src="https://www.loom.com/embed/66a186cac15246a984ae140dde9fcc8f" frameborder="0" width="1112" height="834" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>8341112Loomhttps://www.loom.com8341112https://cdn.loom.com/sessions/thumbnails/66a186cac15246a984ae140dde9fcc8f-89f827a97809ea47.gif77.866This Loom demonstrates the platform for tracking, evaluating, and fixing agents. The speaker runs a test agent and explains how a Python agent-utilized SDK intercepts the call between the agent and supported LLMs, specifically Entropiq and OpenAIR, extending it to a FastAPI backend. The backend evaluates the data, saves results to MongoDB, and renders them in a React frontend, showing runs with traces marked as failed or worked. Finally, it evaluates feedback with evals so users can review outcomes from the run.