MLflow
Open-source AI engineering platform for experiments, evaluations, observability, and model management.
# MLflowpip install mlflownpx mlflow --helpWhat is MLflow?
MLflow is an open-source AI engineering platform for tracking experiments, evaluating agents and LLM apps, managing models, and monitoring production systems. It is increasingly relevant to teams moving agents from prototypes into production.
Experiment tracking
MLflow tracks parameters, metrics, artifacts, and runs across experiments.
Agent teams need to compare prompts, models, tools, and datasets over time.Evaluation workflows
MLflow supports evaluation workflows for ML, LLM, and agent applications.
Repeatable evaluation is the difference between a promising demo and a maintainable product.Production AI platform
The platform includes model management and operational workflows.
Teams can connect agent experimentation to the broader AI engineering lifecycle.What teams use it for
Tags & capabilities
How it stacks up
When to choose MLflow
Compare it with nearby tools by looking at hosting model, integration surface, license, and whether the official docs show the workflow you need.
Questions
Is MLflow open source?
Yes. The repository is listed under the Apache-2.0 license.
Is MLflow an agent framework?
No. It is better understood as an AI engineering platform that can support agent development and operations.