Libraries
TFHE-rs ↗
A pure rust implementation of the TFHE scheme for boolean and integer arithmetics over encrypted data.
Concrete ↗
TFHE Compiler that converts python programs into FHE equivalent.
Concrete ML ↗
Privacy preserving ML framework built on top of Concrete, with bindings to traditional ML frameworks.
fhEVM ↗
A fully homomorphic encryption protocol to write confidential smart contracts.
Services
Coming soon
fhEVM Coprocessor
Deploy confidential applications on Ethereum and other L1s.
Coming soon
TKMS
A fully fledged Threshold Key Management Service for secure FHE key generation and ciphertexts decryption.
Solutions
Confidential AI
Add a layer of privacy to your machine learning workflows and unlock new possibilities, like private inference, confidential training, and IP protection.
Asset Tokenization
Unlock the power of tokenization while ensuring complete confidentiality and security for your assets.
Confidential Networks
Launch a blockchain network with complete asset confidentiality and security.
Confidential Stablecoins
Enhance stablecoin projects with compliant confidentiality.
Decentralized AI
Train and infer on encrypted data without decryption to maintain confidentiality throughout the AI processing lifecycle.
Got a FHE use case?
Contact our team to get started.
Take Zama 5-Question
Developer Survey
Improve Zama libraries, documentation, and resources to help other developers create the future of privacy-preserving applications using Fully Homomorphic Encryption (FHE).