Accelerating reliable software releases for a large property and casualty insurance firm
A Canadian property and casualty insurer faced slow, unpredictable software release cycles driven by fragmented QA processes. Highspring helped transform its testing approach with AI-enabled analysis, modern tooling, and a balanced test pyramid to accelerate delivery and strengthen software quality.
The Challenge
A leading Canadian property and casualty insurance firm struggled to deliver reliable software releases across the enterprise. Fragmented and manual QA processes combined with an over-reliance on unstable UI tests, low coverage, and frequent test failures made each release stressful and unpredictable. Maintaining these fragile tests required substantial effort that slowed development cycles and increased risk exposure. These inefficiencies limited confidence in software quality, delayed feature delivery, and created challenges in meeting business priorities.
Our Solution
Highspring partnered with the insurance firm to implement a QA transformation solution designed to reshape the company’s testing strategy. By enabling AI as an accelerator with Power BI, teams analyzed and reverse-engineered existing end-to-end tests to remove duplicates and refocus scenarios on the most probable client and user journeys based on real usage statistics.
This process also allowed teams to extract and clarify business rules that had been buried within fragile UI tests, scripts, and workflows. Those rules were then re-expressed through clean, maintainable backend and API-supported tests. Together, these changes established a QA strategy built on a balanced test pyramid, modern tooling, and data-driven workflows—delivering a framework that was both trusted and easier to scale.
Our Impact
The partnership helped the insurance firm accelerate and strengthen software releases across the enterprise while improving reliability and confidence in testing outcomes. Key outcomes included:
- 60% faster testing cycles: Critical workflows were executed in significantly less time.
- 95% reduction in test flakiness: Automated tests became far more reliable and predictable.
- 90% improved test coverage: A balanced test distribution ensured robust validation across critical scenarios.
These gains allowed development teams to spend less time troubleshooting unstable tests and more time delivering meaningful improvements to the business.
