MLflow is an open-source AI engineering platform designed to manage the full lifecycle of machine learning and LLM applications, spanning from experiment tracking and model evaluation to deployment and observability. It caters to AI/ML engineers, data scientists, and organizations aiming for production-ready tracing, evaluation, prompt management, and integration with a wide range of AI agent frameworks and ML libraries. MLflow is widely adopted, deeply integrates with popular AI/ML ecosystems, and is backed by the Linux Foundation.
Visit MLflow's official website for product details and getting started.
Comprehensive guides on how to use MLflow for tracking experiments, managing models, and deploying them.
Access the source code, report issues, and contribute to MLflow on GitHub.