How Strise Prevents KYC Failures With AI Agents

KYC is a minefield of changing regulations, edge cases, and brittle integrations. Strise knew they couldn’t afford testing gaps—but also didn’t want to hire a whole QA team. This is how they automated critical coverage across their onboarding and monitoring flows—without slowing down a single release.

The Company

Strise builds KYC software for regulated industries, where bugs can cause compliance issues. Their QA team is small and the complexity was growing faster than E2E tests could cover. With QA.tech, they now rely on AI agents to maintain end-to-end test coverage across complex workflows. They now catch regressions early, without hiring more QA testers.

Company: B2B SaaS

Integration: Github

Time Saved: 256h

Test case executions: 3622

Before:

E2E coverage gaps, not confident in deployments, hours wasted on manual test maintenance.

After

Full E2E coverage, confidence in deployments, AI agents maintain tests.

Strise makes KYC compliance software and their clients are banks and fintechs. They rely on Strise to automate onboarding, risk checks, and continuous monitoring. If something at Strise breaks, their can’t onboard new users.

A small QA team can’t cover everything

Testing KYC workflows before deploying to production is hard. Workflows change often, inputs come from various sources, and the number of edge cases is high. Strise had a small QA setup, relied mostly on E2E tests, and they kept having the same issues:

  • New features weren’t covered by the testing suite
  • Tests were failing silently
  • Too much time was spent maintaining test scripts

Hiring a full QA team wasn’t an option, but neither was shipping a product they weren’t confident in.

How Strise implemented QA.tech

Strise used QA.tech to offload test generation and maintenance to AI agents. The agents were pointed at core parts of the product such as onboarding flows, document parsing, and monitoring dashboards. They successfully built up coverage autonomously, without interference of the QA team.

Tests now run on every PR via GitHub Actions. The team tracks test status in CI like they would any other check.

Results of using QA.tech

  • Stronger E2E coverage without increasing team size or wasting QA hours
  • Catching issues earlier, and easier handling of dynamic data changes
  • No slowdown in shipping, even as the product requirements grew and became more demanding

All the repetitive QA tasks are now offloaded, and Strise focuses on building features with a lot of confidence in the quality of the output.