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Preparing your blockchain forensics platform...
Preparing your blockchain forensics platform...
When a subject address moves after the trace, that movement is evidence. Webhook-driven capture on monitored addresses, KYT screening on a five-minute cadence, and alerts that open an investigation record — so post-seal activity is captured, not missed.
Monitoring tools for litigation teams, investigators, and compliance operations — every capture feeds the same record the exhibit is sealed from.
Notifications when monitored addresses send or receive funds, delivered from Alchemy webhook infrastructure as events land on-chain — event-driven capture, not polling.
Monitor wallets across the 7 live chains — Ethereum, Polygon, Arbitrum, Optimism, Base, Avalanche, and Tron — from a single dashboard. One unified view of all activity.
KYT screening runs every 5 minutes; watchlist briefings summarize the activity that matters. Briefings are narrative aids — the deterministic screening engine makes the determinations.
Set thresholds for transaction amounts, counterparty risk levels, or specific address interactions. Trigger alerts only for activity that matters to the matter.
Receive alerts via email, Slack, SMS, or webhook. Route different alert types to different channels based on severity and urgency.
High-risk activity opens an investigation record with transaction context pre-populated — the capture step feeds directly into the chain of evidence.
Monitor addresses across the 7 live chains from a single unified dashboard, with webhook alerts powered by Alchemy infrastructure. A chain is listed live only once real fetches are proven.
Real-time address monitoring and custody-relevant event capture. One of the 6 forensic agents that carry evidence from first trace to sealed exhibit — its watch work feeds the same case record.
AI-generated summaries highlight the most important activity across your watchlist. KYT screening runs every 5 minutes; briefings never override the deterministic engine's determinations.
Alerts are prioritized by risk level, transaction context, and historical patterns so examiners focus on what matters to the matter.
Machine-learning diagnostics flag unusual transaction behavior — rendered as disclosed diagnostic signals, never silent verdict drivers.
Custody-relevant events, captured and recorded. Start with a free preliminary trace — engagements are scoped per matter on a Statement of Work, not a standing subscription.