Federated Learning Data Marketplace Development

A secure, on-chain protocol for managing data contributor onboarding, task orchestration, and incentive distribution. Built with Solidity and audited for vulnerabilities, ensuring trustless and transparent operations.

Deployable node infrastructure that executes federated learning models locally on contributor data. Implements secure multi-party computation (SMPC) or homomorphic encryption to guarantee raw data never leaves the source.

Centralized, secure service for aggregating encrypted model updates, managing model versions, and ensuring consensus on the global model. Features role-based access control and full audit trails.

White-labeled web portal and developer SDKs (Python, JS) for data owners to easily connect datasets, manage consent, monitor contributions, and claim rewards. Reduces integration time for partners.

RESTful and GraphQL APIs for data consumers (AI teams) to publish training tasks, monitor progress, and pull finalized models. Includes comprehensive usage analytics, billing hooks, and API key management.

Built-in tooling for GDPR/CCPA data rights fulfillment, immutable audit logs for all marketplace transactions (on-chain and off-chain), and automated reporting for regulatory compliance.

Enable secure, privacy-preserving data collaboration. Our platform allows data owners to contribute to ML models without exposing raw data, unlocking new revenue streams while maintaining full compliance with GDPR and CCPA.

Access diverse, high-quality training datasets on-demand. Reduce the time spent on data acquisition and preparation from months to weeks, allowing your data science teams to focus on innovation and iteration.

Leverage a decentralized compute network for federated training. Eliminate the capital expenditure of building massive centralized data lakes and the associated storage/compute overhead, shifting to a scalable operational model.

Every data contribution and model update is immutably recorded on-chain. Provide stakeholders with transparent audit trails for data lineage, model fairness, and contributor compensation, building institutional trust.

Deploy with confidence using our battle-tested architecture. Built with secure multi-party computation (SMPC) patterns, confidential computing, and regular third-party audits (e.g., Trail of Bits) to protect your most sensitive assets.

Avoid vendor lock-in with our flexible, modular platform. Integrate with leading blockchain networks (Ethereum, Polygon, Solana) and ML frameworks (TensorFlow, PyTorch), ensuring your marketplace evolves with the ecosystem.