Secure, production-ready smart contracts built by Web3 experts for your protocol.
We architect and deploy custom smart contracts that form the foundation of your on-chain logic. Our team delivers audit-ready code for ERC-20, ERC-721, and complex DeFi primitives, ensuring security and gas efficiency from day one.
Deploy a secure, tested contract suite in as little as 2 weeks.
Our development process ensures reliability:
OpenZeppelin libraries and industry-standard security patterns.Hardhat or Foundry.Our protocol engineering team delivers production-ready federated learning coordination layers. We focus on secure, scalable, and verifiable infrastructure that enables collaborative AI without centralized data aggregation.
Our Federated Learning Coordination Protocol delivers measurable results, from accelerated model development to enhanced data security and governance.
Reduce time-to-market for AI models by up to 70% by coordinating distributed training across siloed data sources without centralization. Our protocol orchestrates secure, efficient model updates from thousands of edge devices.
Maintain full regulatory compliance (GDPR, HIPAA) with on-chain audit trails. Data never leaves its source; only encrypted model updates are aggregated, providing cryptographic proof of privacy-preserving training.
Build and scale a sustainable network of data contributors. Our tokenomics and smart contract-based coordination provide fair, transparent incentives, ensuring high-quality, continuous participation for model improvement.
Deploy with confidence using our battle-tested smart contracts, audited by leading security firms. Implement granular, multi-signature governance controls for model parameters, participant onboarding, and fund distribution.
Choose the right engagement model for your federated learning protocol, from initial proof-of-concept to full-scale enterprise deployment.
| Feature / Deliverable | Proof-of-Concept | Production-Ready | Enterprise Scale |
|---|---|---|---|
Protocol Architecture Design | |||
Core Smart Contract Suite | Basic MVP | Full Suite | Full Suite + Custom Modules |
On-Chain & Off-Chain Coordination | Limited Scope | Full Integration | Full Integration with Optimizations |
Security Audit & Penetration Testing | Internal Review | Third-Party Audit | Third-Party Audit + Formal Verification |
Node Operator SDK & Documentation | Basic | Comprehensive | Comprehensive + White-Glove Onboarding |
Multi-Chain Deployment Support | Single Testnet | 2 Production Chains | Unlimited Chains + Custom Bridges |
Performance & Load Testing | Up to 100 Nodes | Unlimited Scale Testing | |
Ongoing Protocol Upgrades & Maintenance | Ad-hoc Support | 12-Month SLA | Dedicated Engineering Team |
Typical Timeline | 4-6 Weeks | 8-12 Weeks | 16+ Weeks |
Estimated Investment | $25K - $50K | $80K - $150K | Custom Quote |
A structured, four-phase approach to deliver a production-ready Federated Learning Coordination Protocol, ensuring security, scalability, and seamless integration with your existing ML stack.
We design a custom FL protocol architecture tailored to your data privacy requirements (horizontal/vertical FL) and model complexity. Deliverables include a technical specification, on-chain incentive mechanisms, and a detailed integration roadmap.
Development of secure, gas-optimized smart contracts for participant onboarding, model aggregation, and incentive distribution. Built with Solidity 0.8+ and OpenZeppelin libraries, followed by a comprehensive security audit.
We provide lightweight, documented SDKs (Python/JS) for your data silos to connect to the coordination layer. Includes secure local training loops, encrypted gradient submission, and result verification.
Managed deployment of the protocol to your chosen network (Ethereum, Polygon, Avalanche) with a full monitoring dashboard. We track model convergence, participant performance, and protocol health metrics in real-time.
Our protocol foundation is engineered for enterprise-grade federated learning. We deliver battle-tested, audited components that ensure privacy, security, and seamless interoperability from day one.
Optimized node client with sub-second block times and 10,000+ TPS capacity. Supports both permissioned and permissionless network configurations for flexible deployment.
Comprehensive TypeScript/Python SDKs with full documentation. Includes pre-built adapters for PyTorch and TensorFlow, reducing integration time from months to weeks.
Get clear, specific answers to the most common questions about developing and deploying a secure, production-ready federated learning protocol.
A production-ready federated learning protocol with core coordination, aggregation, and incentive mechanisms typically takes 6-10 weeks from kickoff to mainnet deployment. This includes 2 weeks for architecture design, 3-4 weeks for core smart contract development, 1-2 weeks for client SDK/API integration, and 1-2 weeks for security audits and deployment preparation. Timeline scales with complexity, such as custom privacy layers (e.g., MPC, ZKPs) or multi-chain support.
Our experts will offer a free quote and a 30min call to discuss your project.