How Strise Strengthened KYC Testing with QA.tech

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.

Company Overview

Strise is a modern compliance platform helping financial institutions streamline Know Your Customer (KYC) processes. Their product brings together onboarding, risk assessment, and monitoring in a single system powered by rich contextual data and automation. Strise serves banks, fintechs, and other regulated industries where compliance isn’t optional—and speed and accuracy matter.

The Challenge

As the Strise team scaled their platform and onboarded larger customers, ensuring accuracy across the KYC flows became critical. Their product deals with a range of edge cases—from validating business ownership across jurisdictions to monitoring entity risk in real time.

Before QA.tech, Strise had a small QA team and relied on traditional end-to-end test automation. But that setup hit a ceiling:

  • New features often shipped without full test coverage due to time constraints.
  • Tests failed silently when data sources changed or APIs returned edge-case responses.
  • Maintaining scripted tests became expensive as the platform evolved rapidly.

The stakes were high. Bugs in onboarding flows or monitoring logic could erode trust or trigger compliance issues.

The Solution

To stay ahead of issues without growing the QA team, Strise adopted QA.tech. The decision was driven by their need to:

  • Continuously test flows that depend on dynamic data and regulatory logic.
  • Catch breakages that aren’t easy to script ahead of time.
  • Offload maintenance of test logic to adaptive systems.

QA.tech was rolled out to cover key parts of the platform, including:

  • Business onboarding (with complex form flows and conditional logic).
  • Risk monitoring dashboards.
  • Data enrichment and document handling modules.

The setup was fast: Strise defined test goals and coverage areas. The AI agents then scanned, mapped, and created tests autonomously. GitHub integration enabled tests to run on every deploy, and teams could track results directly in their CI setup.

Conclusion

Strise now delivers higher-quality compliance software with less manual QA effort. With QA.tech, their team can focus on improving product features while the AI agents handle the heavy lifting of test coverage, detection, and adaptation.

For a business where correctness, auditability, and performance are non-negotiable, QA.tech has become an essential part of how Strise ships software.