Build (d)Apps with Fully Homomorphic Encryption (FHE).
Zama Brings Privacy to Web3 and Web2 Applications
Explore the wide range of new use cases unlocked by FHE.
Enable private, compliant, and auditable stablecoin transactions powered by FHE.
Safeguard the confidentiality of RWA & tokenization on public blockchains and ensure auditory compliance.
Secure decentralized identity management with FHE, ensuring KYC/AML compliance while safeguarding user privacy.
Keep sensitive information of onchain governance encrypted, secure, and private using FHE, while preserving transparency and decentralization.
Empower secure and private health predictions with FHE, enabling compliant and confidential analysis of sensitive medical data.
Enable privacy-preserving credit scoring with FHE, ensuring secure and unbiased evaluations of sensitive financial data.
Perform sentiment analysis on encrypted data to safeguard user privacy, ensuring confidentiality while delivering actionable insights.
Securely process and filter images on encrypted data, maintaining privacy while enabling advanced visual content analysis.
Latest News
The latest updates, announcements, and innovations from Zama.
Introducing Zama's fhEVM Coprocessor
Alongside the release of the fhEVM v0.6, Zama is introducing its fhEVM Coprocessor, a major step towards bringing FHE to blockchain.
You can now deploy your FHE smart contracts on the official Ethereum Sepolia testnet.
Enables FHE confidential smart contracts in any non-FHE enabled chains.
Kinexys by J.P. Morgan Releases a Proof-of-concept Focused on the Financial Sector Leveraging Zama’s Privacy-Preserving Solutions.
Zama successfully demonstrated its FHE technology in J.P. Morgan's Kinexys (formerly Onyx) as part of Project EPIC, focused on tokenized finance with privacy, identity, and composability.
Zama Bounty Program Season 7 is Live!
The Zama Bounty Program offers monetary rewards for tackling specific challenges. We just released the season 7 with new bounties targeting our TFHE-rs, Concrete-ML, and fhEVM libraries.
See on Github ↗Empower secure and private health predictions with Fully Homomorphic Encryption (FHE), enabling compliant and confidential analysis of sensitive medical data.
Enable privacy-preserving credit scoring with Fully Homomorphic Encryption, ensuring secure and unbiased evaluations of sensitive financial data.
Perform sentiment analysis on encrypted data to safeguard user privacy, ensuring confidentiality while delivering actionable insights.
Securely process and filter images on encrypted data, maintaining privacy while enabling advanced visual content analysis.