completed production-ai
Fraud Agent Monitor
LangGraph-based monitoring pipeline with 4 specialized fraud agents, deployed as API and dashboard services on Cloud Run.
Started: March 28, 2026
Completed: April 5, 2026
Evidence & Verification
Metrics and claims on this page are tied to the linked artifacts below (repository docs, experiment outputs, and deployment pages when available).
2
Cloud Run Services
4
Agents
4
Pipeline Stages
8/8
P0 Checks
Tags
fraud-detectionagentslanggraphfastapistreamlit
Technologies
Python LangGraph FastAPI Streamlit Docker
Overview
Fraud Agent Monitor orchestrates four task-specific agents to score suspicious financial behavior and produce analyst-ready output:
- Transaction Analyzer
- Pattern Detector
- Risk Scorer
- Report Generator
Live Deployment
- UI: https://fraud-monitor-demo-5tphgb6fsa-as.a.run.app
- API docs: https://fraud-monitor-api-5tphgb6fsa-as.a.run.app/docs
- Latest ready revisions:
fraud-monitor-demo-00007-5n4fraud-monitor-api-00004-55b
- Traffic split: 100% on latest revisions
API Surface
POST /monitorto execute the full multi-agent orchestrationPOST /agents/{name}/invoketo test an individual agentGET /healthfor graph and runtime checks
Validation Snapshot
Phase 3 automated checks passed 8/8 monitor scenarios, including:
- suspicious wire execution with full trace,
- elevated risk scoring and typology detection,
- SAR report generation output,
- normal payment low-risk behavior.
GitHub Status
- Repository: fraud-agent-monitor
- Latest
maincommit verified on April 5, 2026:2e75f91