FLAI Protocol
Decentralized, Web3-native infrastructure for federated learning. Uses sMPC to preserve privacy, tokenized SubDAO governance for coordination, and pay-per-inference monetization.
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Balkeum Labs builds infrastructure where sensitive data is kept secure while empowering community-owned AI.
Hospitals and enterprises keep life-saving data locked behind compliance walls.
Standards differ across institutions, blocking collaboration and model portability.
Contributors aren’t compensated when their data drives AI.
AI models train without moving raw data. Fully HIPAA/GDPR compliant.
Fair scoring ensures best-quality data earns most.
Proprietary models stay encrypted and can be monetized per query.
Decentralized, Web3-native infrastructure for federated learning. Uses sMPC to preserve privacy, tokenized SubDAO governance for coordination, and pay-per-inference monetization.
Learn More →Enterprise FL framework with TEEs. Peer validation ensures fairness, quorum-based governance builds accountability, and closed-source model access enables monetization.
Learn More →Consumer app where individuals share EHR, wearables, and genomic data securely. Contributors earn stablecoin rewards. Pharma buys federated models as real‑world evidence.
Learn More →TEE + sMPC based federated learning — privacy preserved from training to inference.
Local training across institutions/devices enables compliance with HIPAA/GDPR. Zero raw data movement.
Participant updates are secret‑shared. No party sees others' gradients; coordinates aggregation without a central server.
Weights sealed within TEEs. Supports pay‑per‑inference while protecting IP and user privacy against gradient inversion.