Lavendla’s Journey to Scalable QA with a Lean Team

Lavendla, with 150M SEK turnover and a lean team of four developers, faced scaling challenges with traditional testing. QA.tech’s AI agents replaced rigid scripts, catching issues in real-world user paths and enabling growth without sacrificing quality.

Lavendla logo

Lavendla connects people with therapists, lawyers, and advisors specializing in end-of-life planning across Sweden, Denmark, and the United Kingdom. With 150 million SEK in turnover and over 200 professionals across various roles, Lavendla needed a testing approach that didn’t rely on rigid, hardcoded scripts but instead adapted to real-world user behavior. With a lean team of four developers, they wanted testing that could keep up with their growth without pulling resources from feature development. That’s when they turned to QA.tech.

“Our goal with QA.tech was to move beyond predefined test cases. We wanted a solution that could spot unusual user behavior and catch issues before real users encounter them.”

Challenge

Lavendla’s team had previously been writing tests and used Cypress. Some developers would run Cypress tests locally alongside new code as they developed it, while others set up Cypress to run automated tests in their web environment, often through GitHub or Netlify. While functional, this setup relied heavily on scripted tests and required constant manual oversight, especially as they expanded into multiple markets. Keeping testing to essential workflows left gaps in less common user paths, and without a dedicated QA team, developers juggled testing and feature rollouts, which slowed down both.

Charlie Lindberg, Head of Growth at Lavendla, explains:

“Our goal with QA.tech was to move beyond predefined test cases. We wanted a solution that could spot unusual user behavior and catch issues before real users encounter them. Instead of letting real users experience these errors, we brought in AI agents to detect faults, deviations, and issues. Our collaboration is still in its early stages, but so far, I think it’s working really well,”

They needed a more adaptable approach—one that could keep Lavendla proactive, rather than reactive.

“The platform’s design is incredibly appealing—simple, seamless, and efficient. Just input the URL, and it runs, even suggesting additional tests. It’s very straightforward and streamlined.”

Solution

QA.tech brought a flexible, AI-driven testing approach that went beyond scripted test cases. Instead of relying solely on predefined scripts, QA.tech’s autonomous agents could explore and navigate the platform, catching issues even in rare user flows. Lavendla’s team found the platform simple to use: they could plug in new features without extra scripting, covering paths they hadn’t been able to reach before. Charlie notes:

“The platform’s design is incredibly appealing—simple, seamless, and efficient. Just input the URL, and it runs, even suggesting additional tests. It’s very straightforward and streamlined.”

By partnering with QA.tech, Lavendla gained a way to stay on top of quality without adding headcount or stretching their developers thin.

“We weren’t prioritizing testing before, but QA.tech has given us the ability to focus on it now.”

Results

Although early in the process, Lavendla’s setup with QA.tech has already made an impact. With automated monitoring handling daily checks, Lavendla’s developers can focus on growth and new features, while AI-driven testing has expanded their coverage across key workflows and user paths. This scalable, cost-effective solution has also allowed them to keep their resources focused on what matters.

“We weren’t prioritizing testing before, but QA.tech has given us the ability to focus on it now. Previously, we’d deprioritized testing in favor of building features, but as we scale, downtime impacts us more. Prioritizing testing is critical for us at this stage,” says Charlie. Lavendla’s partnership with QA.tech lets them stay proactive, focused, and ready for the next phase of growth.

Core challenges: 

  • Limited Scalability: The reliance on scripted tests required continuous updates, creating bottlenecks as the platform expanded.
  • Minimal Test Coverage: Lavendla only tested critical paths due to cost and time constraints, risking potential bugs in less common user flows.
  • No dedicated QA team: With a lean team, Lavendla lacked the capacity to conduct comprehensive quality assurance.

Results with QA.tech:

  • Comprehensive Test Coverage: Lavendla now tests a wider range of user paths, catching issues before end users encounter them. 
  • Autonomous Testing: QA.tech’s AI agents detect issues independently, reducing the need for manual oversight.
  • Resource Efficiency: Scalable AI testing lets Lavendla focus on development without the need for a large QA team.