E-commerce Fraud Decisioning
Reviews flagged orders, gathers cross-signal context, and decides ship/hold without slowing legit customers.
RiskReal-time
E-commerce Fraud Decisioning
Polished agent demo — preview
Agent running
Agent thinking
- 1Reading inputs and pulling relevant context across systems…
- 2Building a plan: 4 steps, 2 tools, 1 human approval gate.
- 3Executing steps with progress streaming back to the user.
- 4Decision made. Drafting summary and queuing for review.
This demo is a polished preview. Book a build to see the production version.
The problem
Rule-based fraud systems generate too many false positives. Real customers get blocked; bad orders ship.
What the agent does
- Aggregates device, behavior, history, and address signals
- Reasons about the specific case, not just rules
- Decides — and explains — within sub-second SLAs
Business value
Lifts approval rates by 4 points without raising chargeback losses, recovering meaningful GMV.
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