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Concrete ML is an open-source, privacy-preserving, machine learning framework based on Fully Homomorphic Encryption (FHE).

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Welcome

Get started

Learn the basics of Concrete ML, set it up, and make it run with ease.


What is Concrete ML	Understand the Concrete ML library with a full example.	start1.png	getting-started
Installation	Follow the step-by-step guide to install Concrete ML in your project.	start2.png	pip_installing.md
Key concepts	Understand important cryptographic concepts to implement Concrete ML.	start3.png	concepts.md

Start building with Concrete ML by exploring its core features, discovering essential guides, and learning more with user-friendly tutorials.


Fundamentals	Explore core features.	Built-in models Deep learning	build1.png
Guides	Deploy your projects.	Prediction with FHE Production deployment	build2.png
Tutorials	Learn more with tutorials.	Start here Go further	build3.png

Access to additional resources and join the Zama community.

Refer to the API, review product architecture, and access additional resources for in-depth explanations while working with Concrete ML.

Ask technical questions and discuss with the community. Our team of experts usually answers within 24 hours in working days.

Collaborate with us to advance the FHE spaces and drive innovation together.

We value your feedback! Take a 5-question developer survey to improve the Concrete ML library and the documentation and help other developers use FHE.