ML and GenAI
made simple
Build better models and generative AI apps on a unified, end-to-end,
open source MLOps platform
open source MLOps platform
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Join thousands of users worldwide
Run ML and generative AI projects that solve complex, real-world challenges
What makes MLflow different
Open Source
Integrate with any ML library and platform
Comprehensive
Manage end-to-end ML and GenAI workflows, from development to production
Unified
Unified platform for both traditional ML and GenAI applications
Streamline your entire ML and generative AI lifecycle in a dynamic landscape
- Generative AI
- Deep Learning
- Traditional ML
- Evaluation
- Model Management
- Improve generative AI quality
- Build applications with prompt engineering
- Track progress during fine tuning
- Package and deploy models
- Securely host LLMs at scale with MLflow Deployments
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Run MLflow anywhere
MLflow integrates with these tools and platforms
Get started with how-to guides, tutorials and everything you need
- LLMs
- Deep Learning
- Traditional ML
- Tracking
- Deployment
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Evaluating LLMs
Learn how to evaluate LLMs with MLflow![](img/learning/custom-pyfunc_16_9.png)
Using Custom PyFunc with LLMs
Explore the nuances of packaging, customizing, and deploying advanced LLMs in MLflow using custom PyFuncs.![](img/learning/rag_16_9.png)
Evaluation for RAG
Learn how to evaluate Retrieval Augmented Generation applications by leveraging LLMs to generate a evaluation dataset and evaluate it using the built-in metrics in the MLflow Evaluate API.Join our growing community
14M+ monthly downloads
600+ contributors worldwide
600+ contributors worldwide