How Rainforest QA Helps Qualpay Ship Faster—Without Hiring a QA Team
→ 10+ years using Rainforest QA
→ 0 QA headcount
→ 30 minutes to map test coverage vs. weeks of manual effort
→ 20 minutes saved per test by moving from manual to automated with Rainforest
Qualpay is a payments platform that helps merchants and software vendors integrate payment processing into their existing systems and workflows. In the world of financial services, including payments, “good enough” QA isn’t good enough—one broken flow can have immediate and lasting impact on revenue, trust, and end-user experience.
Qualpay is well aware of this challenge. They have a lean, fully-remote team with six full-time developers, three product team members, and no dedicated in-house QA function. Instead, they’ve relied on Rainforest QA for nearly a decade to keep releases moving while protecting payment flows across all major web browsers.
Over time, Qualpay has expanded from Rainforest’s manual testing model into a growing automated suite—and most recently, they’ve begun using Rainforest’s AI features (like AI Test Planner and AI-driven self-healing) to accelerate coverage analysis and reduce brittle test maintenance.
“Rainforest was quick and easy to use from the beginning,” said Wendy Rice, Senior Product Analyst for Qualpay. “We didn’t have to do a bunch of training. It was very intuitive.” And they’ve seen the positive impact on customers and their business compound over the years. As Wendy puts it, “Being able to catch [bugs] before they roll into production and interrupt your customers’ ability to use a service they are paying for is a huge win.”
“Being able to catch [bugs] before they roll into production and interrupt your customers’ ability to use a service they are paying for is a huge win.”
The Challenge
A lean team with a high-stakes product
Qualpay operates in payments, where customer-facing flows must work smoothly across many different browsers and environments. When you are in the business of moving money, user interfaces must be clear, easy to use, and as frictionless as possible. Any issues introduced into production must be addressed ASAP or you risk damaging that trust and losing business.
About a decade ago, the Qualpay team faced a strategic choice: either invest heavily in building an internal QA function—or find a way to scale testing without adding headcount. Qualpay’s CTO, Jack Duncan, came across Rainforest QA and decided to pursue the automated route.
Cross-browser coverage without the cross-browser tax
When Qualpay first adopted Rainforest, one of the biggest drivers was the need to validate key payment journeys across multiple browsers—without asking product or engineering to spend their release days repeating the same tests in different environments. As Wendy Rice, Senior Product Analyst for Qualpay put it, “I was able to use the Rainforest interface to quickly create additional tests across all major browsers.” This helps the team avoid the need to manually ideate and build QA tests, which can be very time-consuming and keep them from more strategic priorities.
Limited time for manual regression and risk of “familiarity misses”
As the Qualpay team has iterated on their product over time, they’ve bumped into a common challenge: internal teams get used to how the product “usually” behaves. Familiarity bias means they may not notice that a minor change has introduced a bug (or, on the flip side, caused a test to fail without good reason). Qualpay wanted a test approach that could surface issues a team that is deeply familiar with their product might miss—especially in nuanced, customer-facing workflows.
Results & ROI
Off to the races
Once the team had selected Rainforest, they got started on a POC. The Rainforest team provided hands-on guidance and support throughout the early days of implementation and continues to do so today. The team says they saw value quickly and weren’t overburdened with a long, complex installation. “Rainforest was quick and easy to use from the beginning. We didn’t have to do a bunch of training. It was very intuitive,” says Rice.
Faster coverage analysis with AI Test Planner
Recently, one product leader at Qualpay was tasked with mapping out their test coverage gaps—something she’d done manually in a previous job that took at least a week with a colleague working in tandem (so, two weeks of FTE time). With Rainforest’s AI Test Planner, Qualpay was able to generate an initial coverage outline in about 30 minutes, then spend about 45 minutes refining this coverage plan to suit their needs and risk tolerance.
Impact: Faster path from “we should improve coverage” to “here’s exactly what to build next,” with at least 1-2 weeks of manual effort saved.
Release testing becomes hands-off (and easier to debug)
Qualpay continues to migrate manual release tests into Rainforest’s automated platform. One recent example: A test that took ~20 minutes to run manually can now be automated and run in ~15 minutes. That might not seem like a huge difference, but, critically, it’s now hands-off. So the team can set the test to run and work on something else. Rainforest’s AI agents make multitasking possible without sacrificing accuracy.
Moreover, if a test fails, Rainforest provides the evidence needed to investigate quickly (using recordings and visual steps), and Qualpay can pass that context directly to their engineering team through Jira. “It’s helpful to have a big sample of test data the engineers can look at in Rainforest.
This way, engineers can quickly see the bug and create a fix,” says Rice. “Being able to catch those before they roll into production and interrupt your customer’s ability to use a service they are paying for is a huge win.”
As one of Rice’s colleagues put it, “Rainforest gets everyone on the same page. Product, engineering—we can all converge on what’s actually wrong and what’s working.”
Impact: Less time executing regressions, less back-and-forth debugging, and clearer tickets for engineers.
Reduced test brittleness with self-healing
Like many products, Qualpay includes dynamic UI elements (for example, reports that default to today’s date). In traditional QA automation, those types of small changes can create noisy failures and neverending maintenance work. Qualpay has leaned on Rainforest’s self-healing functionality to handle these expected variations without snags and reduce the team’s manual QA efforts.
Impact: Automated tests that stay reliable even when parts of the UI shift frequently by nature and self-healing that saves time vs. manual QA.
Faster releases with automation
Today, Qualpay releases roughly every three weeks, with QA spanning up to two weeks per cycle. Early on, much of that effort required manual testing, which increased the risk of human error and slowed feedback loops. Over time, migrating critical flows into Rainforest’s platform to automate them has steadily reduced the QA burden while improving reliability.
A QA model that scales without headcount
Ten years later, Qualpay still operates without a dedicated internal QA team. Instead, product managers run tests, and engineers review artifacts (like videos) as needed for debugging context. Rainforest’s model—especially the ability to run many tests across many environments—gives Qualpay confidence to keep scaling their product without building a QA department from scratch.
“When you work in payments, the experience has to be very smooth, and it has to work smoothly across whatever browser a customer chooses. Rainforest allows us to make certain, for example, that our reports are rendering correctly for end users, no matter what browser they’re using.” - Wendy Rice, Senior Product Analyst, Qualpay
The Rainforest QA Solution
Cross-browser testing built for payments-grade UX
Qualpay originally selected Rainforest because it made cross-browser testing realistic for a small team. “Rainforest allows us to make certain, for example, that our reports are rendering correctly for end users no matter what browser they are using,” says Rice. Qualpay can run repeatable tests across multiple browsers and quickly pinpoint browser-specific issues—without sacrificing release speed.
No-code test creation that product teams can own
Qualpay describes building automated Rainforest tests as working with “building blocks”—assembling steps in plain language rather than writing and debugging code-based automation. This has made it easier for product managers to own QA without needing specialized automation engineering skills. Qualpay also describes “growing alongside Rainforest,” over the last decade, including making use of new features like AI Test Planner to speed up additions to their test suite and reduce manual efforts.
Faster issue communication with Jira artifacts
When failures happen, Qualpay can share recordings and step-by-step context directly with engineering. That reduces ambiguity (and follow-up questions) compared to tickets that simply say “this doesn’t work.”
Modularization and discernment around test coverage
In the early days, Qualpay’s team learned how to think about tests as reusable building blocks rather than long, brittle scripts. Instead of repeatedly recreating core steps like login, they modularized common actions and focused tests on one or two meaningful behaviors at a time.
While writing tests in natural language lowered the technical barrier for doing this, another very real challenge for many companies is deciding what tests matter and how much area a given test should cover — a process Rainforest supported closely as Qualpay’s QA practice matured. Rainforest provides the data needed to make strategic decisions about which tests to create and deploy and which to scrap because they don’t have a big impact on end-users.
Fresh eyes
Qualpay values how Rainforest can catch issues internal teams may overlook. Rainforest’s external perspective mirrors real customer experiences, including users who may be less familiar with payments workflows. This is true for both the Rainforest platform and the human testers that work with Qualpay via Rainforest.
In payments, even small UI inconsistencies can have outsized impact. Qualpay’s approach is simple: any issue that makes it to production becomes a Rainforest test going forward. Over time, this has created a growing safety net that continuously reduces the risk of regressions in revenue-critical flows — even as the product rapidly evolves.
Looking ahead
In 2026, Qualpay’s next area of focus for QA is increasing test coverage—especially for platform areas that historically couldn’t be automated but now can be using Rainforest. AI Test Planner is expected to be a key part of that workflow: identifying gaps, prioritizing them, and steadily converting remaining manual release checks into automated coverage.