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Bringing AI in at Mercury

Draft cited context for fraud alerts while engineers own diagnosis

You’re the software engineer. Your team is in the room. Printed Oct 14, 2026.

Faster fraud investigations depend on context that engineers can verify, not summaries they must trust.

The investigation workflow needs to move quickly while preserving the evidence trail behind every fraud decision.

Who you’d be doing this for

“My founder asked why that vendor charge got through, and I had nothing concrete to show them yet.”

Laura Stanescu · Finance Manager

Manages employee card spend for a growing startup and fields questions when suspicious charges appear.

What is at stake

Engineers spend a median 42 minutes assembling context for each suspicious card alert. You must weigh faster investigation setup against evidence that engineers can independently verify.

Why it isn’t already fixed

Every obvious fix costs something else. That’s the part you’d have to decide.

  • investigation speed vs. evidence traceability
  • AI drafting vs. engineer judgment
  • on-call focus vs. review rigor
  • shared workflow consistency vs. local technical context

Why Mercury

Card controls and real-time fraud decisioning protect operating cash for startups using business accounts and employee cards.

Written with these in mind

embedded AI systems buildertechnical workflow designerevidence-first forward deployed engineer

Not your kind of problem? 27 more at Mercury, or browse every organization.

This is the setup. The work is inside.

Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.