

Case study · Fintech
We trained an AI agent on the work of Finverse's QA team. It runs unit, API and regression tests, writes documentation for new features and tells QA what to check by hand.
The client
Finverse is a fintech platform that handles payments and financial data for businesses and financial services.
The product grows fast: every release brings new features.
The challenge
Manual regression took up to three days and slowed down every release. Some critical bugs still reached production.
Classic automated tests weren't enough: every new feature meant rewriting them or adding more.
The solution
We gathered the existing QA cases and a year of the QA team's work into a knowledge base and trained the agent on it. For every new feature the agent writes the documentation, runs the tests and prepares a list of what needs checking by hand. When it finds a bug, it opens a ticket in the team's tracker right away and, once the developer fixes it, re-runs the test and closes the ticket.
Learns from
Produces
The release
Before
3 days
of manual regression every release
After
1 hour
of regression, run by the agent
Results
"With the new QA process we release with confidence every two weeks. The core financial flows are stable: no regressions, no surprises."
Product Owner, Finverse
We build AI agents trained on your team's work: tests, documentation and checks, with a fixed price in writing before we start.
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