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Most fraud detection platforms are trained on self-labeled data, crowdsourced reports, or synthetic patterns. Deconflict is different. We’re trained on verified law enforcement intelligence. Investigative agencies provide wallet addresses confirmed as fraudulent through active cases. Our models learn from real threats, not assumptions—delivering ground-truth accuracy unavailable elsewhere.
Leverages advanced onchain behavioral analytics to identify anomalous activity and detect potential risk before conventional systems can respond.
Identifies offchain connections and relationships that would otherwise be missed, revealing fraud networks, coordinated operations, and social engineering patterns before they reach your users.
Traditional tools react to fraud after it happens. Deconflict identifies fraudulent wallets in real-time by analyzing behavioral patterns that match active law enforcement cases.
Our platform continuously monitors onchain and offchain activity to expose coordinated schemes, money-muling operations, and sophisticated fraud patterns across:
When fraudulent wallets are detected, our system delivers precise alerts with full investigative context:
Prioritize responses with behavioral factors, onchain evidence, and law enforcement pattern matching
Auto-generated case summaries with regulatory documentation for compliance workflows
Coordinate securely with investigative partners and compliance teams
Our models learn from confirmed law enforcement cases, producing ground-truth accuracy unavailable anywhere else.
Advanced typology recognition links wallet activity, social vectors, and transactional patterns across multiple threat surfaces.
Unified risk visibility across all participants — from exchanges and fintechs to law enforcement and financial institutions.
Zero-PII data design, end-to-end encryption, and regulatory compliance built into every layer.
Our platform empowers institutions to act on verified intelligence, protecting users, assets, and reputation with the same insights trusted by global law enforcement.
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