We deliver custom Solidity and Rust smart contracts with formal verification and comprehensive audit readiness. Our code is built on battle-tested patterns from OpenZeppelin and Solmate to ensure security from day one.
LABS
Services
Zero-Knowledge Machine Learning at Edge
We build systems where ML models run at the edge—on devices or local servers—and generate zero-knowledge proofs to verifiably commit results to a blockchain. This preserves model and data privacy while providing cryptographic trust for DePIN and IoT applications.
Chainscore © 2026
overview
CORE SERVICE
Smart Contract Development
Secure, production-ready smart contracts built to your exact specifications.
Reduce your time-to-market from months to weeks with our modular development approach.
- Token Systems: Custom
ERC-20,ERC-721, andERC-1155implementations with advanced features like vesting, staking, and governance. - DeFi Protocols: Automated Market Makers (AMMs), lending/borrowing pools, and yield aggregators with gas-optimized logic.
- Enterprise Logic: Multi-signature wallets, access control systems, and upgradeable proxy contracts using
UUPSorTransparent Proxypatterns. - Full Lifecycle Support: Development, testing (
Hardhat/Foundry), deployment, and post-launch monitoring.
key-features-cards
ZKML AT THE EDGE
Core Technical Capabilities We Deliver
We architect and deploy production-ready zero-knowledge machine learning systems that run inference directly on edge devices, delivering verifiable AI with enterprise-grade performance and security.
01
On-Device ZKML Model Deployment
We specialize in porting and optimizing TensorFlow/PyTorch models to run inside zk-SNARK circuits on resource-constrained edge hardware (mobile, IoT). Our toolchain ensures verifiable inference with minimal latency overhead.
< 2 sec
Avg. Proof Gen
10-100x
Model Size Reduction
02
Custom zkVM & Circuit Design
We build bespoke zkVMs (e.g., RISC Zero, SP1) and hand-optimized Circom/Halo2 circuits for your specific ML workloads. This includes privacy-preserving model validation and confidential data processing pipelines.
Circom/Halo2
Circuit Frameworks
Audited
Security Standard
03
End-to-End Privacy Architecture
We design full-stack systems where sensitive data never leaves the edge device. Private inputs are processed locally, with only a ZK proof of the valid result submitted on-chain, ensuring data sovereignty and compliance.
GDPR/CCPA
Compliance Ready
Zero Leakage
Data Guarantee
04
Cross-Platform SDK & Tooling
We deliver lightweight SDKs for iOS, Android, and embedded systems that abstract ZK complexity. Includes tools for model conversion, proof batching, and seamless integration with L1/L2 blockchains.
Rust/WASM
Core Stack
2-4 weeks
Integration Time
05
Performance Optimization & Benchmarking
Our engineering focuses on reducing proof generation time and size. We implement recursive proofs, GPU acceleration, and custom gate designs to make ZKML viable for real-time applications.
50-90%
Gas Cost Reduction
Sub-Second
Verification Time
06
Production Monitoring & SLAs
We provide 24/7 monitoring dashboards for proof success rates, edge node health, and system throughput. Backed by 99.9% uptime SLAs and dedicated engineering support for critical deployments.
99.9%
Uptime SLA
< 15 min
Mean Response
benefits
DELIVERABLES
Business Outcomes for Your DePIN or IoT Project
Our Zero-Knowledge Machine Learning at Edge service translates advanced cryptography into tangible business advantages. We deliver verifiable, private, and efficient intelligence directly on your devices.
01
Verifiable Data Integrity
Generate cryptographic proofs for sensor data and ML inferences at the edge. Eliminate trust assumptions in your data pipeline and enable secure, automated settlement for DePIN rewards.
100%
Proof Integrity
On-Device
Proof Generation
02
Reduced Operational Costs
Process and validate data locally with ZK proofs, slashing cloud compute and data transmission costs by over 70%. Pay only for final proof verification on-chain.
>70%
Cost Reduction
Local
Data Processing
03
Faster Time-to-Market
Leverage our pre-audited ZK circuit libraries and modular SDKs for common IoT/ML tasks. Deploy a verifiable inference pipeline in weeks, not months.
< 4 weeks
Initial Deployment
Pre-Audited
Circuit Libraries
04
Regulatory & Privacy Compliance
Enable data monetization and cross-border operations without exposing raw data. Our ZKML architecture is designed for GDPR and similar privacy frameworks by default.
GDPR-ready
By Design
Zero-Trust
Data Sharing
05
Enhanced Network Security
Protect your DePIN from Sybil attacks and faulty nodes with provable ML-based attestations. Ensure only legitimate hardware contributes to the network and earns rewards.
ZK-Attestation
Node Identity
Automated
Slashing Logic
06
Scalable On-Chain Integration
Our lightweight proof verification contracts are optimized for Ethereum, Polygon, and other EVM chains. Handle millions of daily proofs with minimal gas overhead.
EVM Native
Verification
< 200k gas
Avg. Proof Verify
ZKML at the Edge
Structured Development Packages
Compare our tiered packages for developing and deploying verifiable machine learning models on edge devices.
| Capability | Proof of Concept | Production Ready | Enterprise Scale |
|---|---|---|---|
Custom ZK Circuit Design | |||
Edge Device Integration (Raspberry Pi, Jetson) | 1 Device Type | 3 Device Types | Custom Fleet |
On-Device Inference & Proof Generation | |||
Verification Smart Contract (EVM) | Basic | Optimized, Multi-Chain | Custom Logic & Oracles |
Model Privacy (FHE/MPC Options) | Selective | Full Suite | |
Performance SLA (Proof Generation Time) | N/A | < 5 seconds | < 2 seconds |
Dedicated Security Review & Audit | |||
Infrastructure & Monitoring Dashboard | Basic Logs | Full Metrics & Alerts | Custom Dashboard + SLA |
Ongoing Support & Maintenance | 3 Months | 12 Months | 24/7 with 4h SLA |
Estimated Timeline | 4-6 Weeks | 8-12 Weeks | Custom |
Starting Price | $25,000 | $80,000 | Custom Quote |
use-cases
ENTERPRISE-READY USE CASES
Proven Applications Across Industries
Our zero-knowledge machine learning at the edge framework delivers verifiable intelligence where data is generated, enabling new business models and compliance guarantees across sectors.
01
Fraud Detection in FinTech
Deploy ZK-verified ML models directly on mobile devices for real-time transaction analysis. Maintain user privacy while proving fraud risk scores to the network, reducing false positives by up to 40%.
< 100ms
On-device inference
40%
False positive reduction
02
Supply Chain Provenance
Verify product authenticity and ethical sourcing with edge-based sensor data (temperature, location). Generate immutable, privacy-preserving proofs of compliance for each logistics milestone.
End-to-end
Audit trail
Real-time
Compliance proof
04
Autonomous Vehicle Validation
Provide cryptographic guarantees for sensor fusion and decision-making algorithms running in vehicles. Prove safe operational boundaries were adhered to for insurance and regulatory compliance.
Sub-second
Proof generation
Plonk & Halo2
Proving systems
05
Decentralized Identity & KYC
Perform biometric verification and risk assessment locally on user devices. Issue reusable ZK credentials that prove KYC completion without revealing underlying personal data.
Reusable
ZK Credentials
Off-chain
Sensitive processing
how-we-deliver
CORE SERVICE
Smart Contract Development
Secure, production-ready smart contracts built by Web3 experts to power your dApp.
We architect and deploy audit-ready smart contracts on EVM-compatible chains (Ethereum, Polygon, Arbitrum) and Solana. Our development process ensures gas optimization, upgradability patterns, and comprehensive test coverage from day one.
Deliver a secure, functional MVP in as little as 2-4 weeks with our streamlined development sprints.
- Custom Logic:
ERC-20,ERC-721,ERC-1155, DeFi protocols, DAO governance, and bespoke business logic. - Security-First: Built with
OpenZeppelinlibraries and hardened against common vulnerabilities before formal audit. - Full Lifecycle: From architecture and development to deployment, verification, and ongoing maintenance.
Technical & Commercial Considerations
Frequently Asked Questions on ZKML at the Edge
Get clear, specific answers to the most common questions from CTOs and product leads evaluating Zero-Knowledge Machine Learning for edge deployment.
A standard ZKML edge deployment takes 4-8 weeks. This includes 1-2 weeks for requirements scoping and circuit design, 2-4 weeks for development and on-device integration, and 1-2 weeks for security audit and final deployment. Complex models or custom hardware integrations can extend this timeline, which we define in a fixed-scope project plan before engagement.
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