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Artificial IntelligencePilotFraud and anomaly detection

Fraud and anomaly detection — Utilities

Graph and sequence models catching fraud and process anomalies in real time. Delivered for a utilities client in Chennai.

Location
Chennai
Year
2024
Duration
15 weeks
Team
12 engineers
Interactive 3D · drag to rotate
81%
fraud caught
−48%
false positives
16k
tx per second

The challenge

Data existed but lived in spreadsheets and legacy systems, so decisions were made on instinct rather than evidence.

What we built

We owned the whole stack — hardware, firmware, models and dashboards — using XGBoost, Graph ML, Kafka so there was one accountable team.

Delivery timeline

  1. Phase 1

    Discovery sprint and site survey

  2. Phase 2

    Prototype built and tested in the Motera lab

  3. Phase 3

    Pilot on site with before/after measurement

  4. Phase 4

    Scale-out, training and handover

Highlights

  • Designed, built and supported from Motera, Ahmedabad
  • Safety case reviewed with the client's EHS team
  • Remote monitoring and over-the-air updates included
  • Documentation, drawings and source handed over at close

Have a problem that needs a machine built for it?

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We reply to every enquiry within one business day.