CasePilot Real-Time AI Financial Forensics

CasePilot is an event-driven financial forensics platform built for modern fintech environments where fraud unfolds in seconds. Traditional rule engines generate alert noise but fail to expose coordinated patterns across accounts, devices, and locations. CasePilot turns raw transaction streams into structured investigations by combining real-time ingestion, graph analysis, and AI-assisted case generation. The system ingests live transactions and risk signals, aggregates related alerts into single investigative units, and assigns dynamic risk scores. A graph network module maps relationships between users, wallets, devices, and IP addresses to expose mule rings and shared infrastructure. A geospatial velocity engine calculates distance and implied travel speed between events to detect impossible travel and account takeover scenarios. An integrated AI copilot operates in context of the active case. It synthesizes transaction logs, entity links, and historical outcomes retrieved through vector search to generate structured investigative reports and Suspicious Activity Reports. When analysts resolve cases, their decisions are embedded back into the system as structured memory, allowing future investigations to benefit from prior outcomes and reducing false positives over time. CasePilot is designed as a full-stack, real-time investigative workspace: a command center dashboard for monitoring, an interactive graph for tracing fraud networks, geospatial visualization for anomaly detection, and an AI layer that converts evidence into actionable enforcement. The result is a system that shortens investigation cycles, improves detection of coordinated fraud, and creates a continuously learning audit trail.