We architect and deploy production-ready smart contracts on EVM and Solana, delivering audit-ready code from day one. Our development process integrates security-first patterns from OpenZeppelin and Solmate to mitigate vulnerabilities before the first line is written.
LABS
Services
Fraud Pattern Detection AI with On-Chain Data Feeds
We build and deploy custom AI/ML models that analyze transaction graph patterns to generate real-time risk scores, feeding directly into your smart contracts or oracle network to automatically flag and mitigate fraud.
Chainscore © 2026
overview
CORE SERVICE
Smart Contract Development
Secure, audited smart contracts built for production by Web3-native engineers.
Reduce your time-to-audit by 40% with our battle-tested development framework and comprehensive pre-audit review.
- Custom Logic: Build
ERC-20,ERC-721, staking pools, vesting schedules, and custom DeFi primitives. - Gas Optimization: Achieve up to 30% lower gas costs through efficient storage patterns and bytecode optimization.
- Full Lifecycle Support: From initial spec and
Hardhat/Foundrytesting to mainnet deployment and upgrade management via transparent proxies.
We provide verified source code on Etherscan/Solscan and detailed technical documentation, ensuring your team and users have complete transparency. Partner with us to launch with confidence.
key-features-cards
PRODUCTION-READY AI
Core System Capabilities
Our fraud detection system combines proprietary machine learning models with real-time on-chain data to secure your transactions and protect user assets.
01
Real-Time Transaction Screening
Analyze every transaction in under 200ms using live mempool and on-chain data feeds to flag malicious activity before it's confirmed.
< 200ms
Analysis Latency
24/7
Monitoring
02
Anomaly & Pattern Detection
Identify sophisticated attack vectors—from flash loan manipulations to wash trading—using models trained on billions of historical transactions.
99.5%
Detection Accuracy
50+
Attack Patterns
03
Custom Risk Scoring Engine
Receive a dynamic risk score (0-1000) for each wallet and transaction, enabling automated, rule-based actions like blocking or requiring MFA.
1000-point
Risk Scale
Custom Rules
Flexible Actions
04
Multi-Chain Data Aggregation
Correlate threat intelligence across Ethereum, Solana, Polygon, and Base. Detect cross-chain arbitrage attacks and fund laundering.
10+
Networks Supported
Unified API
Single Integration
05
Smart Contract Behavior Analysis
Monitor for deviations from expected contract behavior, including unauthorized privilege escalation and logic exploits in real-time.
Bytecode Analysis
Method
Proactive Alerts
Response
benefits
MEASURABLE IMPACT
Business Outcomes for Your Protocol
Our AI-powered fraud detection system delivers concrete, quantifiable results that directly enhance your protocol's security, user trust, and operational efficiency.
01
Proactive Threat Neutralization
Real-time detection and automated mitigation of sophisticated attack vectors like flash loan exploits, MEV bots, and wash trading before they impact your treasury or users.
< 500ms
Detection Latency
24/7
Monitoring
02
Reduced Financial Loss & Risk
Directly protect protocol assets and user funds by identifying malicious transaction patterns, significantly lowering the financial impact of exploits and fraudulent activities.
> 95%
Attack Pattern Accuracy
Pre-emptive
Action
03
Enhanced User Trust & Retention
Build a safer ecosystem with transparent security metrics. Users and liquidity providers gain confidence from verifiable, AI-backed protection, driving long-term engagement.
Auditable
Threat Logs
Real-time
Risk Scoring
04
Optimized Operational Efficiency
Automate manual monitoring and investigation tasks. Our system provides prioritized alerts and forensic reports, freeing your team to focus on protocol development and growth.
90%
Alert Noise Reduction
Automated
Incident Reports
05
Actionable On-Chain Intelligence
Move beyond simple alerts. Receive structured, labeled data feeds of wallet clusters, behavior graphs, and threat actor profiles for strategic decision-making and compliance.
Structured
Data Feeds
Chain-Agnostic
Analysis
06
Regulatory & Compliance Readiness
Maintain detailed, auditable records of suspicious activity detection and mitigation actions, supporting compliance with evolving DeFi and financial regulations.
Immutable
Audit Trail
Comprehensive
Reporting
A Cost-Benefit Analysis for Technical Leaders
Build vs. Buy: Fraud Detection Solutions
Compare the total cost of ownership, time-to-market, and risk profile of developing fraud detection in-house versus using Chainscore's AI-powered on-chain data feeds.
| Factor | Build In-House | Chainscore AI Feeds |
|---|---|---|
Time to Production | 6-12+ months | 2-4 weeks |
Initial Development Cost | $250K - $750K+ | $0 (No upfront dev) |
Ongoing ML Model Maintenance | 2-3 Data Engineers | Fully Managed |
On-Chain Data Coverage | Limited to your contracts | 50+ chains, 100M+ addresses |
Fraud Pattern Library | Start from scratch | Pre-trained on 10K+ attack vectors |
Real-time Alert Latency | Build your own pipeline (< 1 min) | < 5 seconds SLA |
Security & Audit Overhead | High (Unaudited custom logic) | Low (Continuously audited) |
Integration Complexity | High (Custom API/Infra) | Low (REST/Webhook APIs) |
Total Cost (First Year) | $500K - $1M+ | Starting at $60K/year |
how-we-deliver
PREDICTIVE, PROVEN, PRODUCTION-READY
Our Delivery Process
We deliver a production-grade fraud detection system in weeks, not months. Our phased approach de-risks integration and ensures immediate operational value.
01
Phase 1: Data Pipeline & Model Design
We architect your on-chain data feeds, integrating with Etherscan, The Graph, and proprietary Chainscore nodes. Our data scientists design the initial AI model based on your specific threat vectors (e.g., wash trading, flash loan exploits).
10+ Sources
Data Feeds Integrated
2-3 weeks
Initial Design Sprint
02
Phase 2: Model Training & Validation
Using historical blockchain data, we train the detection model against known attack patterns. We validate accuracy with a >95% true positive rate on test datasets and establish baseline performance metrics for your review.
>95%
Detection Accuracy
< 1 sec
Inference Latency
03
Phase 3: API & Integration Deployment
We deploy the trained model as a secure, low-latency REST API or WebSocket stream. We provide comprehensive SDKs and documentation for seamless integration into your trading engine, wallet, or compliance dashboard.
99.9% SLA
API Uptime
Full SDKs
Python, JS, Go
04
Phase 4: Continuous Monitoring & Tuning
Post-deployment, we monitor model performance and retrain with new data bi-weekly. We provide a real-time dashboard for alert review and false-positive reporting, ensuring the system adapts to evolving threats.
24/7
Performance Monitoring
Bi-weekly
Model Updates
security
CORE SERVICE
Smart Contract Development
Secure, production-ready smart contracts built by Web3-native engineers.
We architect and deploy custom Solidity/Rust smart contracts that are secure by design. Every contract undergoes a multi-stage audit process, including automated analysis, manual review, and formal verification for critical logic.
- Custom Tokenomics & DeFi Logic: Design and implement
ERC-20,ERC-721, staking, bonding curves, and automated market makers. - Gas-Optimized Execution: Achieve up to 40% lower gas costs through efficient data structures and assembly-level optimization.
- Proven Security: Adherence to
OpenZeppelinstandards and battle-tested patterns to mitigate reentrancy, overflow, and governance attacks. - Full Audit Trail: Deliver comprehensive documentation, NatSpec comments, and a verifiable deployment history on Etherscan.
From a technical specification to a mainnet deployment with verified source code, we handle the entire lifecycle. Our engineers ensure your contracts are not just functional but are a resilient foundation for your protocol's growth.
Fraud Pattern Detection AI
Frequently Asked Questions
Get clear answers on how our AI-driven on-chain monitoring service integrates, performs, and scales to protect your protocol.
Our system combines supervised learning on a labeled dataset of 10,000+ historical exploits with unsupervised anomaly detection. It analyzes real-time on-chain data feeds—transaction graphs, gas patterns, smart contract interactions—to identify deviations from normal user behavior. The models are retrained weekly with new threat intelligence, achieving a 99.2% detection rate for known attack vectors and flagging novel patterns with 85% confidence for analyst review.
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