Wallet clustering
Heuristic + ML
Groups wallets that share operational patterns or ownership.
Map wallet relationships, clustering, and transaction flows to uncover counterparties and hidden networks. Teams preparing public token launches with responsibilities ranging from smart contract readiness to liquidity, compliance, and community updates. Detect anomalies, suspicious approvals, and governance changes before funds are at risk. US remains the largest source of institutional crypto volume and venture-backed launches.
Wallet clustering
Heuristic + ML
Groups wallets that share operational patterns or ownership.
Case exports
GraphML, JSON, PDF
Share investigation results with stakeholders or regulators.
Ethereum Mainnet profile
Deepest liquidity and broadest institutional adoption.
Base fees typically 15–40 gwei outside of NFT drops; priority fees ~1–2 gwei.
Graph visualizations connecting wallets via token transfers, LP shares, and governance activity. Entity tagging with metadata (team, treasury, exchange, MEV, mixers). Flow timelines to trace funds across chains and protocols.
Need repeatable deployment workflows across multiple networks. Zero critical issues reported post-launch.
Uniswap, Lido, EigenLayer, and Aave drive high-value flow and require precise gas timing. Live monitoring of contract upgrades, proxy changes, and admin key usage.
Live monitoring of contract upgrades, proxy changes, and admin key usage. Teams must evidence internal controls and retain comprehensive activity logs for potential subpoenas.
Token scanner sweeps of newly listed assets interacting with your treasury. Teams must evidence internal controls and retain comprehensive activity logs for potential subpoenas.
Mapping transacting wallets to known entities for counterparty risk scoring. Teams must evidence internal controls and retain comprehensive activity logs for potential subpoenas.
Yes. Upload CSV or JSON cluster definitions to align with internal intelligence.
We overlay public attribution datasets and allow custom enrichment via API.
Graph rendering dynamically loads segments to keep performance stable even with thousands of nodes.