Shipping an AI support agent for a fintech
Illustrative example — a representative project, not a specific client engagement. Replace with a real case study before launch.
Approach
An illustrative look at building an AI support agent for a fintech: ground an LLM in the company's real help content, wire it into the existing ticketing system so it resolves routine questions and escalates edge cases with full context, and ship a tight MVP first. The goal is faster first responses and a support team freed to handle the hard cases.
A fast-growing fintech's support inbox was scaling faster than the team. Customers waited hours for answers to questions the docs already covered, and agents burned out on repetitive tickets.
- 1
Grounded an LLM agent in the company's real help content and policies using retrieval, so answers stayed accurate and on-brand.
- 2
Wired the agent into the existing ticketing system so it could resolve, tag, and escalate — never going rogue on sensitive actions.
- 3
Built guardrails and a human-in-the-loop review for anything touching money or accounts.
- 4
Shipped a tight MVP first, measured deflection and satisfaction, then expanded coverage based on real transcripts.
Replace “TODO” with the real, verifiable numbers you're comfortable sharing.
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