Enabling encrypted learning, verifiable contributions, and decentralized control through advanced Federated Learning, Fully Homomorphic Encryption, and Blockchain Provenance.
Federated Learning
Train AI across institutions, silos, or devices —
without sharing raw data.
Cifer moves models, not data, enabling
decentralized training in untrusted environments
with complete local control.
Run encrypted computation without ever decrypting.
Cifer integrates FHE into real workflows, allowing
zero-trust learning on sensitive inputs without
compromise.
Blockchain Provenance
Log contributions, model updates, and training
activity on-chain — when enabled.
Cifer ensures tamper-evident audit trails and
verifiable participation without relying on
centralized oversight.