Katalon, an AI-augmented software testing company, claims to have developed and launched “the world’s first fully AI-native automated testing system that learns directly from real user behaviour.”
Unlike conventional tools, TrueTest does not rely on pre-scripted assumptions, the firm stressed. It continuously analyses live production usage to generate and maintain test coverage that truly matters, freeing teams from the limitations of legacy test automation.
“Model-based test automation was built on guesswork. We end that era,” said Vu Lam, CEO of Katalon. “This isn’t just our vision. It is shaped by our customers, who asked for a smarter path to quality.”
As AI-generated code accelerates software development cycles, quality assurance has increasingly become a bottleneck.
Manual test creation and maintenance are time-consuming and difficult to scale.
According to Katalon’s 2025 State of Software Quality Report, 61% of QA teams are now adopting AI tools to reduce repetitive tasks, while nearly half report having to update up to 30% of their test scripts regularly just to keep up with product changes.
The solution directly addresses these challenges, the firm claimed. Rather than basing tests on theoretical user flows, static requirement documents, or stakeholder input, the platform captures real user interactions in live production environments.
It analyses this behaviour to identify business-critical workflows and automatically generates tests that reflect how applications are actually used.
Broader shift
Katalon’s launch of TrueTest reflects a broader shift in the software testing landscape.
The industry is moving toward solutions that are intelligent, adaptive, and aligned with real-world usage. In this new era, where speed of release and product quality are both non-negotiable, traditional script-based automation is no longer sufficient.
As applications evolve, TrueTest continuously adapts the test suite without human input, removing the need for time-consuming script rewrites or test maintenance, said Lucio Daza, Vice President of Product Marketing at Katalon.
“We’re putting an end to guesswork in testing,” declared Florida-based Daza.
Asked why this solution is so different than other platforms out there, he stressed: “This isn’t a repackaged AI tool. It’s a ground-up rethinking of how testing should work in an AI world, shaped by everything we’ve heard from customers who wanted smarter coverage, less guesswork, and more impact beyond QA.”
Daza said TrueTest was designed from the ground up for today’s AI-native development environments. It uses live production data to generate test coverage and updates itself in real time, making it far more agile than traditional tools.
Rather than focusing on hypothetical use cases, it identifies and prioritizes test coverage based on actual user behavior. This ensures that QA teams are always focusing on the most important and most-used parts of an application, he said.
By creating a continuously self-maintaining test environment, Daza claimed TrueTest is able to eliminate the need for engineers to spend countless hours updating scripts every time a feature changes.
It also provides a unified view of user journeys and application health, giving QA, development, product, and marketing teams shared insight into how their software performs in the real world.
Admittedly, Katalon’s approach has led to some new strategic partnerships and the firm was able to share some big name-endorsements.
Prasad Siddaiah, practice head of Test Automation at Wipro, said TrueTest adds “a new layer of intelligence” to the automation stack.
He noted that by using production insights to automatically generate and maintain test coverage, enterprises can move from reactive testing to proactive quality orchestration.
Meanwhile, Amalesh Mishra, chief growth officer at QualityKiosk Technologies, highlighted that TrueTest helps eliminate a common bottleneck in CI/CD pipelines.
By generating and updating tests based on real user behavior, his teams have been able to remove the hidden cost of test maintenance and focus on enabling smarter quality engineering, Mishra said.
Intense pressure
The launch of Katalon’s latest platform is another good example of how quality assurance professionals are leaning into AI faster than ever.
That shift is fuelled by both urgency and intent, researchers found in the above-mentioned Katalon’s 2025 State of Software Quality Report.
They concluded that as AI reshapes expectations, 82% of QA professionals say AI skills will be critical in the next 3 to 5 years, and teams are already adapting.
“The shift toward AI-powered testing isn’t just accelerating, it’s inevitable,” said Lam. “It validates what we’ve long believed: QA professionals, the unsung heroes of software innovation, are navigating intense pressure to move faster without compromising quality, and their impact is finally being recognised.”
He added: “Looking ahead, the future of quality will belong to teams who can combine AI fluency with human insight to lead testing into a smarter, more adaptive era.”
Lam also pointed out that those with higher AI fluency excel not just at using new tools, but in test planning, problem-solving, and applying AI concepts in real-world scenarios.
To close the skills gap, two out of every three teams are investing in continuous learning, while more than half are adopting AI-driven testing practices to stay ahead.
And for the most advanced teams, QA is no longer just a safeguard, it is a business enabler. In fact, three out of four respondents say aligning QA with business goals has helped improve customer retention.
Katalon’s report surveyed over 1500 quality professionals, from engineers to senior executives, across North America, Europe, and Asia-Pacific.
The report explored the challenges, capabilities, and innovations shaping today’s testing landscape–and how QA teams are evolving from execution-focused roles to strategic drivers of business value.
The research team found that testers who blend AI, automation, and manual testing skills with critical thinking are leading the next wave of innovation in software quality.
“High-maturity QA teams that leverage these hybrid testers are 1.3 times more likely to adopt AI-augmented test optimisation and 1.8 times more likely to implement intelligent test maintenance practices like self-healing tests, compared to lower-maturity teams,” the report stated.
Moreover, they said that “happier” QA pros aren’t just more satisfied, they’re more effective.
According to the report, they’re 1.4 times more likely to implement advanced automation solutions and 1.4 times more likely to say AI has improved efficiency and automation in their roles.
“As organizations modernise, there is a clear connection between job satisfaction and innovation in software quality,” the team wrote.
When looking at AI and the future of QA, AI-driven testing is gaining momentum, with 61% of QA teams adopting it to automate repetitive tasks and free up time for more strategic work.
Forward-looking teams are embracing advanced automation tools, augmented with AI, with the potential to make testing more adaptive, efficient, and intelligent.
Beyond AI, they are also investing in performance and load testing tools (34%) and test management platforms (30%) to further optimize workflows and scale quality with confidence.
Finally, the research showed that high-performing teams are modernising on three critical fronts: 61% are adopting AI-driven tools, 51% are using modern development practices, and 40% are investing in continuous testing.
“Together, these shifts are accelerating release cycles while preserving what matters most: trust, reliability, and quality at scale,” the report concluded.
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