12 / Quality, cloud & infrastructure
Regression checked on every change, not once a quarter
We build and maintain automated test suites a team actually trusts — running in CI, with the cost of maintenance worked out up front.
Manual regression has a fixed price: several days of a team's time before every release, and a quiet agreement that when things get rushed, less gets checked. The bigger the system, the more often that price is paid by cutting scope — and the defect surfaces at the customer.
Automation only solves that when the tests are maintained like production code. So we start from what is worth automating rather than from a tool: critical paths and repeatable regression go to the suite, one-off scenarios stay manual. The suite is written in Python with PyTest, version-controlled in your repository and run in the pipeline on every change — with a report you can read without an interpreter.
In the environments at PwC, Roche and E.ON where the firm's founder worked, a test suite is part of the release rather than a side project next to it — and that is exactly how we treat it here. We are equally direct about the limit: if maintaining a test would cost more than it is worth, we don't propose it.
What the service covers
A framework and a first working suite
You come out of this stage with tests that actually run: the test project structure, environment configuration, test data and a suite covering the paths the business earns money on. No heroic coverage of "everything" — coverage of what hurts.
- Approach and test project structure
- Environment and test-data setup
- A smoke suite for the critical paths
- Readable execution reports
API and integration tests
The cheapest tests in a suite and usually the best value: they check contracts between systems, response codes, validation rules and scenarios spanning several services — without the brittleness typical of interface tests.
- REST endpoint and contract tests
- Scenarios spanning several systems
- Authorisation and input-validation tests
Interface tests and visual regression
UI tests where they genuinely belong — on purchase, sign-in and form-completion paths. We write them to survive a layout change: selectors based on roles and data attributes rather than element order.
- Critical user-path tests
- Form and validation tests
- Cross-browser execution
Running in CI/CD
Tests nobody has to remember to run. We wire the suite into the pipeline (GitHub Actions), set quality gates on pull requests and nightly full-regression runs, and route the results to where the team already looks.
- Quality gates on pull requests
- Nightly regression and on-demand runs
- Result notifications for the team
Rescuing a suite nobody believes
A suite with half the tests disabled, where a red build stops nobody, is worse than no tests at all — it creates the illusion of control. We take those over: diagnose the causes of instability, fix or delete the tests carrying no value, and get the suite back to a state where a red build means something again.
- Diagnosing and fixing flaky tests
- Removing tests with no diagnostic value
- Cutting suite execution time
- Handover of the suite to the client's team
Typical situations
A full manual regression pass takes the team days, so before an urgent release it simply doesn't happen.
Automated tests exist, but they've been red for months and nobody looks at them any more.
You release several times a week and need a gate that stops a change from breaking payments.
The team can write code, but has nobody to set up a test framework that stays maintainable.
What you can count on
- Regression runs automatically on every change — without blocking days of the team's time.
- You know what the suite covers, what it deliberately does not, and what it costs to maintain.
- A red build means something again, so the team reacts to it instead of routing around it.
- Tests in your repository, written like production code — your team can take them over at any point.
Technologies
- Python
- PyTest
- REST API testing
- SQL
- GitHub Actions
- CI/CD
Questions about this service
Fewer than people assume. A dozen or so tests on the paths that generate revenue — sign-in, basket, payment, a key form — pay for themselves within a few releases, because they replace the most repetitive part of the manual work. Full coverage is rarely a sensible goal and we don't propose it by default.
No, and that isn't the point of it. Automation guards what repeats; a person finds what nobody wrote into a scenario. Automation frees a tester from clicking through regression so they can explore new features instead — and that is the right division of labour.
Usually yes, but we start by answering whether it's worth it. We review the suite and you get a short report: what works, what is unstable, what tests nothing meaningful, and how much work stands between the project and a usable state. If writing a basic suite from scratch is faster and cheaper, we say so plainly.
You decide. The tests live in your repository, they're documented and written in a standard stack, so your team can take them on — and the handover includes walking through the structure and the rules for adding new cases. You can also keep suite maintenance on our side.
Related services
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DevOps and cloud
CI/CD, Docker, Terraform and AWS, so releases become a single click and you hear about failures before your customers do.
Technical audits
Audits of code, applications, websites, QA processes and infrastructure. Instead of opinions and reassurances, a written report with priorities and an action plan.
Let's work out what is worth automating in your project
Tell us what regression looks like before a release today and what you've already tried. You'll get a concrete answer: what we'd automate first, what we wouldn't, and why.