We architect and deploy custom smart contracts that power your core business logic. Our focus is on security-first development, gas optimization, and regulatory compliance for tokens, DeFi protocols, and enterprise applications.
LABS
Services
Privacy-Preserving AI Model Coordination for Predictive Maintenance
We implement federated learning and secure multi-party computation protocols on blockchain to enable collaborative training of predictive maintenance AI models on encrypted IoT data without exposing sensitive operational information.
Chainscore © 2026
overview
CORE SERVICE
Smart Contract Development
Secure, production-ready smart contracts built for scale and compliance.
Deliver a battle-tested, audited contract suite in 2-4 weeks, not months.
- Security Audits: Every contract undergoes rigorous review using
SlitherandMythril, following OpenZeppelin standards. - Protocol Expertise:
ERC-20,ERC-721,ERC-1155,ERC-4626, and custom standards for DeFi, NFTs, and RWAs. - Full Lifecycle Support: From architecture and development to deployment, verification, and ongoing maintenance with 99.9% uptime SLAs.
key-features-cards
PRIVACY-FIRST AI INFRASTRUCTURE
Core Technical Capabilities We Deliver
We build the secure, scalable, and verifiable coordination layer for AI models, enabling decentralized collaboration without compromising data sovereignty.
benefits
DELIVERABLES
Business Outcomes for Your DePIN Platform
We architect and implement the privacy-preserving infrastructure that enables secure, scalable, and compliant AI model coordination on decentralized physical infrastructure networks.
01
Secure Multi-Party Computation (MPC) Orchestration
Deploy MPC protocols that allow AI models to be trained and inferred upon across distributed DePIN nodes without exposing raw data. We implement industry-standard frameworks like SPDZ and ABY3 to ensure cryptographic security.
End-to-End
Data Privacy
Zero-Knowledge
Proof Integration
02
Federated Learning Coordination Layer
Build a decentralized coordination layer for federated learning that manages node selection, model aggregation, and incentive distribution. Our systems handle heterogeneous hardware and variable network conditions common in DePINs.
>95%
Model Accuracy Retention
< 24 hrs
Aggregation Cycle
03
On-Chain Verifiable Compute
Integrate verifiable computation (zk-SNARKs/STARKs) to generate cryptographic proofs of correct AI model execution on DePIN hardware. Enables trustless verification of work for transparent reward distribution.
Sub-Second
Proof Verification
Auditable
Compute Logs
04
Tokenomics & Incentive Mechanism Design
Design and implement token-based incentive systems that align node operator participation with network goals. We create staking, slashing, and reward distribution smart contracts tailored for AI/ML workloads.
ERC-20/4626
Standard Compliance
Dynamic
Reward Models
05
Cross-Chain Data Availability
Implement robust data availability solutions using EigenDA, Celestia, or Ethereum blobs. Ensures training datasets and model checkpoints are persistently accessible for decentralized verification and recovery.
99.9%
Data Uptime SLA
Cost-Optimized
Storage
06
Compliance & Audit-Ready Architecture
Build with privacy-by-design principles for GDPR, CCPA, and sector-specific regulations. We provide comprehensive audit trails, data provenance tracking, and role-based access controls for enterprise clients.
SOC 2
Framework Ready
Immutable
Audit Logs
Infrastructure Decision Matrix
Build vs. Buy: Coordinating Privacy-Preserving AI
A detailed comparison of the costs, risks, and time investments between developing your own privacy-preserving AI coordination layer versus leveraging Chainscore's managed service.
| Key Factor | Build In-House | Chainscore Managed Service |
|---|---|---|
Time to Production | 6-12+ months | 4-8 weeks |
Initial Development Cost | $250K - $750K+ | $50K - $150K |
Core Expertise Required | MPC, ZK-SNARKs, Federated Learning, Blockchain | Integration & Application Logic |
Security & Audit Overhead | High (Unaudited Custom Code) | Low (Pre-Audited, Battle-Tested Framework) |
Ongoing Maintenance & Updates | Dedicated 3-5 person team | Fully Managed with Optional SLA |
Model Coordination Features | Basic Orchestration | Multi-Party Compute, Verifiable Inference, Slashing |
Supported Privacy Frameworks | Custom Implementation | ZKML (zkSNARKs/STARKs), FHE, Secure MPC |
Uptime & Reliability SLA | Self-Managed (Your Risk) | 99.9% Uptime Guarantee |
Total Cost of Ownership (Year 1) | $500K - $1.2M+ | $80K - $200K |
Best For | Large Enterprises with Dedicated Crypto Research Labs | FinTechs, Web3 Startups, & Scale-ups |
how-we-deliver
PROVEN FRAMEWORK
Our Implementation Methodology
We deliver production-ready, privacy-preserving AI coordination systems using a structured, four-phase approach. This ensures predictable delivery, clear milestones, and a secure, scalable outcome tailored to your specific data governance and model requirements.
01
Architecture & Protocol Design
We design the cryptographic protocol and system architecture, selecting optimal primitives (ZK-SNARKs, FHE, MPC) for your use case. This phase defines the trust model, data flow, and on/off-chain components.
1-2 weeks
Design Sprint
3+ Options
Architecture Reviewed
02
Secure Implementation & Auditing
Our team builds the core coordination logic and privacy layers. Every component undergoes rigorous internal review and is prepared for external security audits by firms like Trail of Bits or Quantstamp.
100%
Code Review
Certified
Audit Ready
03
Integration & Orchestration
We seamlessly integrate the privacy layer with your existing AI/ML pipelines and data sources. This includes deploying smart contracts, backend services, and client SDKs for model participants.
< 2 weeks
Typical Integration
Multi-Chain
EVM & Beyond
04
Production Deployment & Monitoring
We manage the go-live process and provide ongoing monitoring dashboards. Track model accuracy, participation, gas costs, and system health with enterprise-grade observability tools.
24/7
Monitoring
99.9% SLA
Uptime
Privacy-Preserving AI Coordination
Frequently Asked Questions
Get clear answers on how we build secure, decentralized AI systems that protect data and model integrity.
Our engagement follows a structured 4-phase process: 1) Discovery & Scoping (1 week) to define requirements and architecture. 2) Development & Integration (3-5 weeks) to build the MPC/TEE modules and smart contracts. 3) Security Audit & Testing (2 weeks) including internal review and third-party audits. 4) Deployment & Support (1 week). Most projects are delivered in 6-8 weeks from kickoff to mainnet deployment.
ENQUIRY
Get In Touch
today.
Our experts will offer a free quote and a 30min call to discuss your project.
NDA Protected
Confidentiality24h Response
Time to ValueDirectly to Engineering Team
No Sales Fluff10+
Protocols Shipped
$20M+
TVL Overall