For years, Katalon has provided a practical middle ground between the speed of low-code test automation and the control offered by traditional frameworks.
Does it still support the needs of engineering teams as we accelerate through the last years of this decade and look ahead to the 2030s?
Right now, the answer is – as with the case of any sort of legacy enterprise software – ‘possibly, as long as you’re happy with some pretty major trade-offs.’ When these trade-offs stop being reasonable compromises, and instead become major limitations, will depend on your circumstances.
For most modern teams, though, we’d imagine that tipping point is coming sooner rather than later – if it hasn’t already arrived. Here’s why it’s worth considering Katalon alternatives right now, and a few to base your shortlist around if you are ready to make the switch.
Why Teams are Looking for Katalon Alternatives in 2026
Previously, recorder capabilities, execution speed, and strong reporting features were major selling points for automated testing solutions. Now, they’re pretty much a given.
In 2026, test automation tools really differentiate themselves by their ability to facilitate rapid release cycles and frequent UI updates without generating a massive maintenance workload. And, often, to open up testing processes to non-technical team members.
Katalon doesn’t deal especially well with these issues because:
- It generates a considerable maintenance burden – Katalon’s self-healing features help with this. However, teams spend significant time updating object repositories, refining locators and investigating false failures, which slows release cycles
- It’s AI-enhanced, not AI-native – Katalon’s AI capabilities enhance an existing scripted automation workflow rather than moving toward faster, more intelligent processes overall. This makes it faster, but teams still struggle to keep up with modern release cycles
- Collaboration at scale isn’t easy – While Katalon is low-code, it’s a steep learning curve for non-technical team members. Users need to learn Katalon’s conventions (and have a broad familiarity with automated testing practices) for best results
7 Katalon Alternatives For AI Test Automation
1. Momentic
Momentic is an AI-first Katalon alternative that’s entirely built around intent-driven agentic processes and large language models.
Instead of relying heavily on selectors, Momentic understands applications more like a human tester would . It reasons about page structure, labels, semantics and user intent, allowing tests to remain stable even when underlying implementation details change.
While Katalon does introduce some intent-based testing, its approach is still fundamentally based around selectors like CSS and XPath. This means that Momentic reduces maintenance overhead significantly more than Katalon can.
Momentic also makes more extensive use of agentic AI. If you’re using AI to accelerate code creation, these agentic tools make it far easier to test your code at the pace you are creating it and prevent bottlenecks from building up.
The Features That Make a Difference
Agentic AI
Momentic’s AI takes a more exploratory approach than Katalon’s. This makes it easier to automate previously resource-intense manual processes and remove the bottlenecks they create.
For example, rather than simply returning a negative result on a particular test, Momentic’s AI can suggest a list of possible reasons for the failure, ordered by probability. This saves significant engineering hours investigating the reasons for failure as well as automating the initial process.
Natural language test creation
You describe what you want to test in plain English. The AI builds the test and executes it. It’s that simple.
As well as being the fastest way to create automated tests, this encourages more open collaboration between QA, product managers and developers. Tests are easier to understand during code reviews and release planning than traditional keyword-driven or locator-heavy scripts.
Self-healing tests
Intent-based locators make it easier for the system to update tests when the UI updates. This results in a significantly reduced maintenance burden, fewer false results, and increased engineer trust in your automated test suite.
Best For
- High-velocity teams wanting to accelerate their release cycle
- Engineering-led organizations that want QA embedded in development workflows
- Companies adopting AI-first tooling across their stack
2. QA.tech
Rather than asking engineers to author test scripts, QA.tech is a Katalon alternative that uses autonomous AI agents that explore applications, understand workflows and continuously validate functionality.
Like implementing Momentic, this requires a bit of a shift in processes compared to some of the AI-lite options on this list, but the gains in efficiency, coverage, and product quality make the effort worthwhile.
The Features That Make a Difference
Autonomous agentic exploration
QA.tech navigates your application, identifies workflows, evaluates expected behaviour, and surfaces regressions autonomously. This dramatically reduces the effort required to maintain broad regression coverage.
Easier to scale
Whereas Katalon only works as quickly as engineers create and maintain tests, QA.tech continuously discovers new product behaviour as the application evolves, allowing teams to identify unexpected regressions they may otherwise have missed.
Best For
Teams looking for a Katalon alternative offering a high degree of autonomous testing (and the time savings that come with this).
3. Virtuoso
Virtuoso is one of the most mature enterprise AI automation platforms. Its focus is enabling engineers and product teams to generate and maintain tests using natural language while offering enterprise-grade governance.
Teams with highly specialized requirements may feel trapped by Virtuoso’s relative lack of customization options. Outside of this, the tool helps teams significantly reduce the maintenance burden associated with frequent deployments.
The Features That Make a Difference
Natural language test creation
Virtuoso allows users to build tests using natural language, with the platform translating those descriptions into executable tests. This makes collaboration between technical and non-technical roles considerably easier.
AI-powered maintenance
Like Momentic, Virtuoso significantly reduces maintenance through intelligent element identification and self-healing capabilities. This reduces the maintenance workload generated by frequent UI updates.
Best For
Large engineering orgs looking for gains in efficiency, scalability, and collaboration across multiple teams.
4. Testim
Testim’s hybrid approach combines visual modelling with generated code. This offers a solid balance between the efficiency of AI and the control of code-first automation, allowing customized tests where necessary.
You won’t get the full whack of AI efficiency, but it offers a good balance between speed and flexibility for organizations who don’t want to adjust existing processes too much.
The Features That Make A Difference
Smarter locator stability
Testim evaluates multiple attributes and historical behaviour to locate elements more reliably. This can reduce maintenance compared with Katalon’s Selenium-driven automation.
Easier scaling
Some teams find Testim provides stronger support for reusable components, shared logic and enterprise-level governance than Katalon. If you’re running larger teams, this is especially valuable.
Best For
Enterprise QA organizations seeking AI-assisted automation without rebuilding existing testing practices. Salesforce-heavy teams will appreciate the specialized features in this area.
5. Mabl
Mabl is a continuous release quality platform, combining AI test automation with a range of observability, performance monitoring, and release validation features. This makes it a strong choice for teams looking to ‘shift right’ for continuous production monitoring and rapid post-deployment feedback loops.
You’ll sacrifice some of the flexibility of Katalon, which takes a more developer-first approach. In return, you’ll save the engineering hours you would have spent on manual infrastructure management.
The Features That Make a Difference
Built-in production intelligence
Katalon’s post-deployment monitoring options are limited. If you’d like visibility into performance regressions alongside your test results – and would prefer to do so without integrating multiple platforms – Mabl is a Katalon alternative worth considering.
Intuitive cloud execution
While Katalon offers cloud execution through TestCloud, you still need to manage test projects, execution environments and automation assets as they scale. Mabl’s fully managed SaaS platform offers simpler test authoring, execution, and infrastructure management for cloud-based teams.
Best For
Cloud-native SaaS organizations with mature CI/CD pipelines and continuous observability requirements.
6. Tricentis Tosca
If you’re managing large, business-critical applications or working in highly-regulated industries like healthcare or finance, Tosca remains a go-to choice for its strong governance features and model-based testing approach.
It’s a complex piece of software – even with the numerous agentic AI features it offers – with significant licensing costs. Equally, if you can afford it and have (or can develop) the expertise to use it effectively, it serves specialized governance needs better than any tool on this list.
The Features That Make a Difference
Enterprise governance
Compared with Katalon, Tosca offers significantly stronger capabilities around compliance, auditability, risk-based testing and enterprise portfolio management.
Large-scale enterprise application support
Tosca supports SAP, Oracle, Salesforce and numerous enterprise platforms. Mature integrations for these exceed Katalon's capabilities in many large-scale deployments.
Best For
Large enterprises with complex governance requirements.
7. ACCELQ
ACCELQ is a cloud-native, AI-assisted automation platform focused on enterprise scalability. Its low-code interface enables both technical and non-technical users to contribute to automation while making governance
Like other cloud-native tools, flexibility can feel limited. If you want maximum control over infrastructure or custom code options, opting for a solution you can deploy locally (or one with flexible deployment options like Momentic ) might suit your team a little more.
The Features That Make a Difference
Unified automation across channels
ACCELQ provides a consistent workflow for web, API, mobile and backend automation within a single cloud platform, with a cloud-first architecture that simplifies collaboration across teams.
AI-assisted authoring
ACCELQ emphasizes AI-assisted test generation and optimization a little more than Katalon, helping teams increase coverage while reducing repetitive manual scripting.
Best For
Large organizations seeking collaborative, cloud-based automation at scale.
Momentic: The Best Katalon Alternative for Modern Teams
Momentic’s AI-driven approach allows you to test faster and more extensively than Katalon while shipping fewer bugs to production.
Just ask the team at AI identification platform GPTZero , who accelerated their release cycles by 80% after implementing Momentic. They also saw an 89% decrease in their defect escape rate.
“Momentic is the only solution that shows us when a change disrupts a core feature our users depend on.”
Currently being thwarted by QA bottlenecks and looking for Katalon alternatives?