FHE is a powerful technology that enables computations on encrypted data without needing to decrypt it. This capability ensures user privacy and provides robust protection against data breaches, as operations are performed on encrypted data, keeping sensitive information secure even if the server is compromised.

The Torus framework makes writing FHE programs easy for developers by incorporating a Fully Homomorphic Encryption over the Torus (TFHE) Compiler based on LLVM.

Torus enables developers to efficiently develop privacy-preserving applications for various use cases. For instance, Torus ML is built on top of Torus to integrate privacy-preserving features of FHE into machine learning use cases.