QA & Test Automation
QA and test automation is building the checks that catch defects before your users do. We focus on the paths that matter commercially rather than pursuing a coverage percentage, and we treat reliability as the primary requirement — because a suite that fails at random gets ignored, and an ignored suite is worse than no suite at all.
The problem
When release day needs a room
Release day is a spreadsheet and several people clicking
Somebody maintains the regression script. Before each release the team works through it manually, which takes most of a day, so releases get batched — which makes each one larger and riskier, which makes the manual pass longer. Everyone can see the loop; nobody has time to step out of it.
The suite exists and nobody believes it
There are tests. They fail intermittently for reasons unrelated to the change, so the accepted practice is to re-run the job until it passes. At that point the suite has stopped being a signal and become a delay, and a genuine failure now looks exactly like the noise everyone has learned to dismiss.
It broke in code nobody thought they had touched
The change was reviewed, small, and unrelated. It reached production and something else stopped working. Nobody was careless — there was simply nothing in place that would have connected the two, and the same thing will happen again on a different pair of files.
What a real fix takes
The value of a test suite is not its size, it is whether people believe it. A trusted suite of forty tests changes how a team ships; two thousand tests that fail randomly change nothing except the length of the build. That makes flakiness the central engineering problem in this work rather than a tidying-up task — and the causes are usually structural: timing assumptions, shared state between tests, and test data that leaks from one run into the next. Fixing those is unglamorous, harder than writing new tests, and the entire difference between a suite that survives the year and one that gets skipped in CI by March.
Outcomes
What changes
Regressions caught before release
rather than reported by a customer, particularly in the code nobody thought the change would touch.
Faster releases with less fear
Teams ship more often once the safety net is trustworthy, and smaller, more frequent releases are less risky in themselves.
Tests people actually trust
Flakiness is treated as a defect in its own right, because it is the main reason automation efforts get abandoned.
Manual effort focused where judgement is required
— exploratory testing, usability, edge cases nobody specified — rather than on clicking through the same script every sprint.
What we build
What we build
Test strategy proportionate to your actual risk, automated end-to-end tests for the journeys where failure costs money or trust, API and integration suites, unit coverage where it is missing on genuinely important logic, performance and load testing, accessibility checks, and CI integration so everything runs on every change.
The parts that determine whether the suite lasts are mostly infrastructure rather than tests: isolated test data so runs cannot interfere with each other, stable selectors that survive a redesign, a clean environment per run, and fast enough execution that nobody is tempted to skip it. A suite that takes forty minutes gets bypassed under deadline pressure regardless of how good the tests are.
What you receive
What you receive
The test suite itself, in your repository alongside the code it tests, running in your CI on every change — not in a separate tool or an account we hold.
With it, the test strategy that decided what got automated and what deliberately did not, the fixtures and data setup that let the suite run from a clean state, and whatever was needed to make the application testable in the first place — stable selectors, seeding, environment configuration. Your team writes tests in the same patterns afterwards, which is the point; a suite only we can extend has a short life.
How it works
How it works
Identify what actually matters
The journeys where failure is expensive — checkout, signup, payment, the core task your product exists to perform. Broad shallow coverage is worth less than deep coverage of these.
Automate the critical paths first
, so protection arrives before the full suite does.
CI integration
, so tests run on every change rather than on request.
Flake elimination
, treated as its own workstream rather than as cleanup — timing, shared state, data isolation.
Handover
, so your team writes tests in the established patterns going forward.
Typical engagement is four to eight weeks to establish a working suite, with critical-path tests usually delivering value in the first two or three weeks. The phase that takes longest on an existing application is making it testable at all — adding stable hooks, separating test data, getting a clean environment — and that work is invisible in a demo while determining everything that follows.
Technology
What we work with
Technologies we work with, chosen to fit your application and your CI rather than applied uniformly.
End-to-end: Playwright or Cypress.
Unit and integration: whatever is idiomatic for your stack. Introducing a second testing framework alongside one your team already knows is rarely worth the friction.
Load and performance: k6 or comparable, run against a realistic environment rather than a laptop.
CI: your existing pipeline, extended. Tests that live outside the pipeline get skipped.
Where this applies
Where this applies
Strongest where releases are frequent, where a regression has already caused real damage, or where manual regression testing has become the bottleneck that sets your release cadence. Common in fintech and retail and e-commerce, where a broken payment or checkout path has immediate and measurable cost.
Weakest on a product still changing shape rapidly. Tests written against an interface that changes weekly cost more to maintain than they save — stabilise the product first, then automate.
Frequently paired with cloud and DevOps, since a deployment pipeline and a trustworthy test suite are two halves of the same capability.
Why us
One team, not three vendors
The usual way
- A strategy consultant, a development shop and a marketing agency, each scoped separately.
- Months spent getting three vendors to agree, and blame to allocate when something breaks.
- The model ships and adoption becomes somebody else's problem.
With Nexiour
- One team across strategy, engineering and growth. You skip the coordination tax entirely.
- We own the whole outcome — from the first audit to the system that is running.
- Delivery across the UK, UAE, Germany and India, with overlapping hours in four markets.
What it costs
How we scope and price
Fixed scope, quoted after reviewing your application and whatever testing exists today. Three things drive it: how many critical journeys are in scope, how testable the application currently is, and whether existing tests need repairing or replacing — inheriting a flaky suite is often more work than starting cleanly, and we will tell you which situation you are in after the review.
Ongoing test maintenance can be retained or handed to your team. Handing it over is the default.
FAQ
Frequently asked questions
Coverage percentage is a poor goal. High coverage of trivial code alongside untested payment logic produces a good number and protects nothing. Target the journeys where failure is expensive and measure protection rather than percentage.
Usually, and it is common work. Flakiness generally comes from timing assumptions, shared state and poor test data isolation. Fixing it is what makes the suite worth having, and it is often the whole engagement.
When the product is still changing shape every week — you would be maintaining tests against a moving target. When the team will not run or maintain the suite, since automation nobody owns decays into noise. When the real problem is that requirements are unclear, because tests written against an ambiguous specification just encode the ambiguity. And when releases are rare and small enough that a short manual pass genuinely covers it; not every team needs this.
Critical-path tests usually deliver value within the first two to three weeks, well before the full suite exists.
Both. Automate the repetitive regression checking; keep people for exploratory testing, usability and judgement. Automation replaces the tedious part, not the thinking part.
Yes. Test automation does not require the application to have been built with testing in mind, though it is faster when it was — and where it was not, some of the engagement goes into making it testable.
Ideally your team, and we build and document with that in mind. Retained maintenance is available where you would rather not.
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