Financial services
Real-time risk intelligence
Streaming machine learning that flags fraudulent activity before it settles — detection moved from overnight batches to the moment money moves.
$40M+
exposure prevented
Sub-second
detection latency
24/7
monitored in production
Challenge
Fraud that settled before anyone noticed
Fraud was caught in overnight batches — hours too late to stop the money leaving.
Approach
Move detection to the moment
We moved scoring into the transaction stream, evaluating events in real time with models that retrain as fraud evolves.
What we built
Streaming ML, governed
A streaming pipeline, a real-time feature store, and monitored ML models with human review for edge cases — observable, explainable, and audit-ready.
Outcome
Caught before it settles
Sub-second scoring now flags fraudulent activity before settlement. Over $40M in exposure was prevented in the first year.
§ Start
Stop fraud
in real time?
Tell us the outcome you need. We'll bring the team to reach it.
"They delivered what three vendors before them couldn't — and they still run it for us."