Description
MLflow is the largest open-source AI engineering platform tailored for agents, large language models (LLMs), and machine learning (ML) models. It empowers teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while effectively managing costs and controlling access to models and data.
With over 30 million monthly downloads, MLflow is trusted by thousands of organizations to confidently deploy AI to production. Its comprehensive feature set includes production-grade observability, evaluation, prompt management, and optimization, as well as an AI Gateway for managing costs and model access. The platform supports a wide range of integrations, including OpenAI, Claude, Gemini, and LangChain, among others.
MLflow's observability capabilities allow users to capture complete traces of their LLM applications and agents, providing deep insights into their behavior. Built on OpenTelemetry, it supports any LLM provider and agent framework, enabling users to monitor production quality, costs, and safety effectively.
The evaluation features enable systematic assessments, tracking quality metrics over time, and identifying regressions before they reach production. Users can choose from over 50 built-in metrics and LLM judges or define their own through flexible APIs. Additionally, MLflow automatically detects issues in traces using AI-powered analysis across various dimensions, including correctness, latency, execution, adherence, relevance, and safety.
For prompt management, MLflow allows users to version, test, and deploy prompts with complete lineage tracking. It also optimizes prompts using state-of-the-art algorithms to enhance performance. The unified API gateway simplifies interactions with all LLM providers, managing rate limits and controlling costs through an OpenAI-compatible interface.
The MLflow Agent Server facilitates the deployment of agents to production with a single command, offering a FastAPI-based hosting solution with automatic request validation and built-in tracing. As a fully open-source platform under the Apache 2.0 license, MLflow is free to use with no vendor lock-in, making it compatible with any cloud, framework, or tool. Its production readiness is validated by its use at scale by Fortune 500 companies and numerous teams worldwide.
MLflow's Core Features
Open Source
Production Ready
Observability
Automated LLM Evaluation
Prompt Management
AI Gateway
Agent Server
Integrations with 100+ AI frameworks
Human Feedback Collection
Cost Tracking
Getting Started with MLflow
Capture traces: Add minimal code to start capturing traces, metrics, and parameters.
Run code: Execute your code as usual while exploring traces and metrics in the MLflow UI.
Deploy agents: Use a single command to deploy agents to production.
Monitor applications: Utilize observability features to track production quality and costs.
MLflow's Use Cases
- AI Application Monitoring
- LLM Evaluation
- Prompt Optimization
- Agent Deployment
- Cost Management
