“Privacy-preserving ML meets verifiable data flows.”
Privacy-preserving ML, zero-knowledge proofs, and resilient network primitives. Designed for verifiable, secure device intelligence at scale.
On-device models with encrypted execution and local adaptation.
ZK proofs certify telemetry integrity across chains and ledgers.
Peer-to-peer orchestration with recovery and consensus primitives.