Think of this as a tireless digital analyst that reviews suspicious financial transactions the way a seasoned compliance investigator would—reading alerts, pulling related data, and drafting a clear recommendation for a human to approve.
Financial institutions spend huge amounts of time and money manually reviewing AML (anti–money laundering) alerts, many of which are false positives. This slows investigations, increases compliance risk, and strains operations as regulatory expectations grow.
Tight integration into existing AML case-management workflows and access to institution-specific alert histories and decisions, which can be used to tune the agents’ behavior and improve performance over time.
Hybrid
Vector Search
Medium (Integration logic)
Context window cost and latency when pulling and summarizing large case histories and transaction records for each alert.
Early Adopters
Positioned specifically for AML alert review workflows rather than generic AI copilots, likely pre-integrated with common financial crime workflows and data structures (alerts, cases, KYC files, SAR narratives).