Detect Energy Theft Faster with Genie
Type
On-Demand Video
Duration
16 mins 13 seconds
See how energy suppliers detect theft faster and optimize recovery with governed AI
Energy providers are under growing pressure to reduce losses, protect customers, and modernize operations as energy theft, fraud, and rising market complexity continue to impact the industry. At the same time, teams need faster ways to turn data into action without compromising governance, trust, or cost control.
In this demo presented by Daniel Zoccali, a Solutions Architect at Databricks, it showcases a closed-loop AI business process for energy theft detection and revenue protection hosted on a Databricks App. You’ll see how energy providers can manage their own ML Models to flag suspicious accounts suspicious accounts, help investigators interpret risk signals, generate dispatch-ready reports, answer executive questions with trusted analytics, and automate board-level reporting on a single governed platform.
What you’ll learn from watching:
- How to identify and prioritize likely energy theft cases from ML models in Databricks
- How business users can interact with data intelligent Databricks Apps
- How to embed AI in the business process to accelerate revenue recovery
- How to deliver trusted KPI answers with Genie Agents
- How to implement enterprise AI governance and cost controls across ML & AI models
