AI product Open source
MLflow is an open-source AI engineering platform for agents, large language models, and machine-learning models, developed in the MLflow repository. It provides experiment tracking for models, parameters, metrics, and evaluation results, along with production observability, evaluation, prompt versioning and optimization, and model lifecycle tools. Its agent and LLM observability captures application traces using OpenTelemetry and supports different LLM providers and agent frameworks; its AI Gateway provides an OpenAI-compatible interface for routing requests, managing rate limits and credentials, handling fallbacks, controlling costs, and applying guardrails. MLflow can be run as a server and accessed through Python, TypeScript/JavaScript, Java, and other programming languages, with integrations including OpenTelemetry and MCP.
2 uses taken from transcripts — each links to the moment in the video.
Tracks experiments in the multi-agent system stack.
An OpenTelemetry-compatible platform for tracing, evaluating, and monitoring multi-agent systems and LLM workflows. It captures inputs, outputs, metadata, tool calls, database queries, token counts, and per-step latency, and supports LLM-as-a-judge evaluations, prompt versioning, and automated quality gates.
2 in the library.