Federated Intelligence
Network (FIN)
The first enterprise AI network where every customer's models improve from collective intelligence — with mathematically proven privacy. No raw data ever leaves your premises. Ever.
How FIN Works
Privacy-preserving collective learning in 4 steps
Opt-In & Enroll
Your tenant enrolls in FIN via a single API call. You select which of your platform models participate. Consent scope is locked to gradient_only — raw data physically never leaves your infrastructure.
Local Training
Your BrainPredict models train on your local data, exactly as they do today. After each training round, differential privacy (ε=1.0, δ=1e-5) adds mathematically calibrated noise to the gradient before it leaves your server.
Secure Aggregation
DP-noised gradient hashes (Dilithium-3 signed, never raw gradients) are aggregated across all FIN participants using Shamir Secret Sharing (3-of-5 threshold). No single party — including BrainPredict — can see any individual contribution.
Better Models, Automatically
Every 24 hours, you download the aggregated model delta. Your models improve from thousands of other enterprises' training signals — without exposing a single byte of your data.
Privacy Guarantees
6 layers of cryptographic protection — no competitors can match this architecture
Zero Raw Data Sharing
Only SHA-256 hashes of DP-noised gradient vectors are transmitted. Raw data, model weights, and business logic never leave your premises.
Differential Privacy
Every contribution is protected by ε=1.0 differential privacy — the gold standard used by Apple, Google, and the US Census Bureau.
Threat Intelligence Sharing
Opt-in to share anonymized cyber threat IOC hashes with sector peers via ThreatHorizon integration. Deters attackers before they reach you.
Platform-Selective Enrollment
Enroll specific platforms (Finance, Supply, Cyber) independently. You control exactly which models participate in FIN.
Shamir Secret Sharing
3-of-5 threshold secret sharing means aggregation requires multiple independent parties — no single point of compromise.
Dilithium-3 Attestation
Every gradient contribution is CRYSTALS-Dilithium-3 signed. The aggregate is provably composed only of legitimate contributions.
Why Competitors Cannot Build This
FIN requires the on-premise zero-knowledge architecture as its foundation
Cloud-First Architecture
Salesforce, SAP, Microsoft AI — all cloud-based. Cloud architecture requires data to pass through external servers. FIN is only possible on-premise where data physically cannot leave.
No On-Premise MPC Infrastructure
Secure aggregation via Shamir Secret Sharing requires a running on-premise Sentinel MPC engine. BrainPredict already has this. Building it from scratch takes 2+ years.
No Differential Privacy Layer
Our ε=1.0 DP implementation is embedded in the BLO federated learning infrastructure. Retrofitting this into cloud AI is architecturally incompatible.
Network Effect Is Self-Reinforcing
The first mover captures the entire network effect. Once 50+ enterprises join FIN, the model quality gap becomes insurmountable for any new entrant.
Join the Intelligence Network
Every enterprise that joins FIN makes the network smarter for everyone — including you. Enrollment is available on all BrainPredict enterprise tiers.