More speed
AI supports assessment, test design, test data, API wiring and triage. Repetitive implementation moves faster while architecture and release stay with the team.
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Migrate test automation faster, keep it under control
Many companies pay high licence fees for mature test automation — and still hesitate to move away from the tool. We migrate regression suites to open, maintainable frameworks. AI accelerates analysis, generation and triage; experienced test engineers own architecture, review and release.
AI does not write tests directly into production for us. We define target architecture, patterns, test data and acceptance criteria first. Generated tests, page objects, API clients and triage suggestions are read, improved and accepted only after a quality gate.
We migrate tests from Tosca, UFT, Ranorex, TestComplete, Katalon or UiPath Test Suite to Playwright, Selenium or Robot Framework. Not by naive conversion, but through inventory, risk mapping, coverage matrix, pilot and controlled parallel runs.
The new automation runs in GitHub Actions, GitLab CI/CD, Jenkins or Azure DevOps — with JUnit reports, Allure, Xray, traces, screenshots and clear quality gates. Failed does not automatically mean product defect: evidence, triage and ownership decide the route back.
The goal is no new vendor lock-in and no permanent consultant dependency. Your team receives code, architecture decisions, runbook, review guidelines and training on the AI-assisted workflow so automation can continue internally.
Why AI-first
Licence savings happen after replacement. Our AI-assisted approach also reduces the effort of the migration itself — without handing quality responsibility to a model.
AI supports assessment, test design, test data, API wiring and triage. Repetitive implementation moves faster while architecture and release stay with the team.
Removing proprietary licences plus reducing manual implementation effort lowers migration cost and makes the business case easier to defend.
Consistent patterns, reviews of every generated change, flaky-test control and CI/CD quality gates create a regression suite releases can trust.
Typical landscapes
Business-critical processes often span multiple systems. We test across UI, API, data and surrounding applications.
AI workflow
A repeatable loop of human instruction, AI generation, expert review and quality gate.
Target architecture, patterns, acceptance criteria and context are set precisely.
Tests, test data, page objects, API clients and triage hints are produced faster.
Correctness, readability, privacy, security and maintainability are checked.
Only reviewed changes enter regression; everything else goes back into iteration.
Approach
Full replacement, staged migration or hybrid transition: the path follows risk, economics and technical fit.
Inventory, risk, coverage, licence model, test data and integrations are analysed and translated into a practical roadmap.
Outcome: decision paper with business caseA representative pilot validates framework, patterns, CI/CD, reporting, Xray/Allure integration and parallel operation.
Outcome: production-ready foundationWe migrate in prioritised waves, stabilise regression and hand over code, docs, review process and training.
Outcome: internally operated test automationFrequent questions
Part of the test logic and test data can often be reused. A robust migration is rarely pure conversion, though: redundant, unstable or proprietary patterns are assessed and rebuilt deliberately.
Through a coverage matrix, representative reference scenarios, pilot runs and a time-boxed parallel run. A domain is replaced only once the agreed acceptance criteria are met.
No. AI produces drafts based on our instructions. Every change is reviewed, optimised and protected by quality gates before it becomes part of production regression.
That depends on your system landscape, browsers, team skills, non-web parts, libraries and operating model. The assessment documents the decision transparently.
No, the goal is full handover. Your team receives code, documentation, runbook, review guidelines and training on the AI-assisted working process.
Revenue system, privacy-first AI or a platform with operational demands — let's talk about your project.