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MLflow

https://mlflow.org/

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Gen AI

Ship high-quality GenAI, fast

Features

Observability Evaluations Prompt Registry

App versioning AI Gateway

Model training

Mastering the ML lifecycle

Features

Experiment tracking Model evaluation

MLflow models Model Registry & deployment
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Gen AI

Ship high-quality GenAI, fast

Features

Observability Evaluations Prompt Registry

App versioning AI Gateway

Model training

Mastering the ML lifecycle

Features

Experiment tracking Model evaluation

MLflow models Model Registry & deployment

Deliver production-ready AI

The open source developer platform to build AI applications and models with confidence.

GenAI Apps & Agents

Enhance your GenAI applications with end-to-end observability, evaluations, AI gateway and tracking all in one integrated platform.

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Model Training

Streamline your machine learning workflows with end-to-end tracking, model management, and deployment.

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Trusted by thousands of organizations and research teams

Integrates with 40+ apps and frameworks

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Choose from two options depending on your needs

Self-hosted Open Source

Apache-2.0 license

Full control over your own infrastructure

Community support

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Managed hosting

Free and fully managed — experience MLflow without the setup hassle

Built and maintained by the original creators of MLflow

Full OSS compatibility

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Summary

MLflow is an open-source platform designed to streamline the entire machine learning lifecycle, from experimentation and model training to deployment and monitoring, now extending its capabilities to GenAI applications. This comprehensive approach enables organizations to accelerate AI development, improve model quality, and ensure production-ready AI solutions, fostering greater confidence and reliability in AI deployments.

MLflow achieves this by offering components for experiment tracking, model management, and deployment, alongside new features tailored for GenAI, such as observability, evaluations, prompt registries, and AI gateways; it supports integration with over 40 apps and frameworks, including PyTorch, OpenAI, HuggingFace, and LangChain, facilitating a unified workflow across diverse tools and environments; the platform's flexibility is further enhanced by offering both self-hosted open-source and managed hosting options, catering to different user needs and infrastructure preferences.