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Full-Stack Web3 dApp Development
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Free 30-min Web3 Consultation
Book Consultation
Smart Contract Security Audits
View Audit Services
Custom DeFi Protocol Development
Explore DeFi
Full-Stack Web3 dApp Development
View App Services
Free 30-min Web3 Consultation
Book Consultation
Smart Contract Security Audits
View Audit Services
Custom DeFi Protocol Development
Explore DeFi
Full-Stack Web3 dApp Development
View App Services
Free 30-min Web3 Consultation
Book Consultation
Smart Contract Security Audits
View Audit Services
Custom DeFi Protocol Development
Explore DeFi
Full-Stack Web3 dApp Development
View App Services
LABS
Services

Zero-Knowledge Machine Learning Library Development

We design, build, and audit specialized ZK-SNARK/STARK libraries and circuits for core ML operations. Deliver verifiable, private inference and training for your AI applications.
Chainscore © 2026
overview
CORE SERVICE

Smart Contract Development

Secure, production-ready smart contracts built by Web3 experts.

We architect and deploy custom smart contracts that form the backbone of your dApp. Our development process ensures security-first design, gas optimization, and full audit readiness from day one.

  • Custom Logic: Tailored Solidity 0.8+ contracts for DeFi, NFTs, DAOs, and enterprise use cases.
  • Security Foundation: Built with OpenZeppelin standards and formal verification patterns.
  • Deployment & Management: Full lifecycle support from testnets to mainnet, including upgradeable proxy patterns.

Deliver a secure, auditable, and maintainable codebase that scales with your protocol's growth, reducing time-to-market by weeks.

key-features-cards
ZKML ENGINEERING

Core Development Capabilities

We architect and deploy production-ready zero-knowledge machine learning systems that are private, verifiable, and performant. Our full-stack approach ensures your ZKML application is built on a secure, scalable foundation.

03

Proving Infrastructure

Deploy scalable proving backends with GPU acceleration. We implement batching, recursion, and distributed proving to achieve sub-2 second proof times for complex models.

< 2 sec
Proof Generation
GPU-Accelerated
Infrastructure
04

On-Chain Verification

Integrate verifier smart contracts with gas-optimized Solidity or Cairo. We ensure cost-effective verification on Ethereum L1, L2s (zkSync, Starknet), and other EVM-compatible chains.

< 200k gas
Avg. Verification Cost
Multi-Chain
Deployment
06

Security & Auditing

Rigorous security review of circuits and smart contracts. Our process includes formal verification of constraints and audits following OpenZeppelin standards to eliminate vulnerabilities.

Formal Verification
Circuit Security
OZ Standards
Audit Process
benefits
EXPERTISE YOU CAN TRUST

Why Partner for ZK-ML Library Development

Building a production-ready ZK-ML library requires deep expertise in cryptography, machine learning, and blockchain systems. We deliver battle-tested, auditable code that accelerates your time-to-market and ensures security.

02

Gas-Optimized Circuit Design

Our engineers specialize in writing efficient ZK circuits for ML operations (matrix multiplications, activations) that minimize on-chain verification costs by up to 70% compared to naive implementations.

≤ 70%
Gas Reduction
R1CS, Plonkish
Constraint Systems
04

Production Deployment & Scaling

We provide end-to-end support from library design to mainnet deployment, including prover/verifier optimization, multi-chain compatibility (EVM, Starknet, zkSync), and horizontal scaling strategies.

EVM, L2s
Chain Support
4-6 weeks
Avg. Time to MVP
ZKML Library Implementation

Structured Development Packages

Compare our structured packages for integrating a production-ready Zero-Knowledge Machine Learning library into your application.

Feature / DeliverableProof of ConceptProduction PilotEnterprise Scale

Custom ZK Circuit Design & Integration

Pre-Trained Model Conversion (e.g., PyTorch → ZK)

1 Model

Up to 3 Models

Unlimited Models

Performance Optimization (Prover Time)

Basic

Advanced (< 5s)

Bespoke (< 1s)

On-Chain Verifier Smart Contracts

Single Chain

Multi-Chain (2)

Multi-Chain (5+)

Comprehensive Security Audit

Internal Review

Third-Party Audit Report

Third-Party Audit + Bug Bounty

Integration Support & Documentation

Basic

Priority

Dedicated Engineer

Ongoing Maintenance & Updates

6 Months SLA

12+ Months SLA

Estimated Timeline

4-6 Weeks

8-12 Weeks

Custom

Starting Investment

$50K - $100K

$150K - $300K

Custom Quote

how-we-deliver
PROVEN METHODOLOGY

Our ZK-ML Development Process

We deliver production-ready ZK-ML libraries through a rigorous, security-first development lifecycle designed for enterprise-grade applications.

01

Requirement & Architecture Design

We begin by mapping your specific ML model (TensorFlow, PyTorch) to an optimal ZK circuit architecture, selecting the right proving system (Groth16, Plonk, Halo2) for your performance and privacy needs.

1-2 weeks
Design Phase
3+ Options
Architecture Reviewed
02

Circuit Implementation & Optimization

Our engineers implement your model in Circom, Noir, or custom R1CS, focusing on constraint minimization and memory optimization to reduce proving costs by up to 70% versus naive implementations.

> 70%
Gas Cost Reduction
Circom/Noir
Primary Frameworks
04

Proving System Integration

We integrate the optimized circuit with a high-performance proving backend (e.g., SnarkJS, Bellman) and a lightweight verifier contract, ensuring sub-2-second proof generation on consumer hardware.

< 2 sec
Proof Generation
< 200k
Gas for Verification
05

SDK & Developer Tooling

We deliver a TypeScript/Python SDK with comprehensive documentation, example dApps, and testing suites, enabling your team to integrate private ML inference in under 2 weeks.

TypeScript/Python
SDK Support
< 2 weeks
Integration Time
06

Deployment & Ongoing Support

We manage the trusted setup ceremony (if required), deploy the verifier to your target chain (Ethereum, Polygon, zkSync), and provide 6 months of support with 99.9% SLA on critical updates.

99.9%
Support SLA
6 months
Included Support
tech-stack
Technical & Commercial Questions

ZK-ML Library Development FAQs

Answers to the most common questions CTOs and technical founders ask when evaluating a partner for zero-knowledge machine learning library development.

A core library with 3-5 standard ZK-ML primitives (e.g., verifiable inference for a CNN, privacy-preserving model training proofs) typically takes 6-10 weeks from spec to audit-ready code. Complex, custom circuits or novel proof systems can extend to 12-16 weeks. We provide a detailed sprint-by-sprint roadmap during discovery.

ENQUIRY

Get In Touch
today.

Our experts will offer a free quote and a 30min call to discuss your project.

NDA Protected
24h Response
Directly to Engineering Team
10+
Protocols Shipped
$20M+
TVL Overall
NDA Protected Directly to Engineering Team