Quality Engineering
We build automated test suites that run on every change, catch regressions the manual pass would have missed, and turn the release decision from a judgement call into a green light.
The problem
They buy it because one of these four has started costing real money, and the cost is compounding.
Every feature you ship adds something else to re-check before the next one. The checklist grows with the codebase. The team working through it does not.
The defect that escapes is rarely in the new feature. It is in the thing that already worked, broken by a change somewhere else, and missed because the manual pass at the end of a long week did not reach that far.
People who are good at finding what nobody predicted are instead working through the same scripted checks they ran last sprint. It is the most expensive possible way to run a checklist.
The release decision gets made on confidence rather than evidence — who tested what, how recently, and whether anyone checked the payment flow again after Tuesday’s change.
Why it compounds
This is the whole argument, and it is structural rather than clever. Each release adds to what must be re-checked. Done by hand, that bill is paid again in full every single time.
Every feature permanently enlarges the regression pass. The only ways to keep release dates are to add testers or to test less — and testing less is how defects reach customers.
Adding a test costs once. Running it costs almost nothing, forever. The suite grows with the product while the time to run it barely moves.
Illustrative shapes, not measured data. The real curve for your codebase is what we establish in the assessment.
How we work
How you release now, where defects actually escape, what your coverage really is. This is also where we tell you what is not worth automating. A test that costs more to maintain than the bug it catches is a liability, and every codebase has some.
What gets checked at unit level, what at API level, and what through the interface. That split is most of the job: interface tests are the slowest and most brittle, so they carry only the cases that genuinely need a browser. We settle test data and environments here too — the thing that quietly stalls most automation projects.
Written in your stack, committed to your repository, reviewed like any other code. Not locked inside a vendor tool you would have to keep paying to read.
Three stages in, you have tests. The last two are what make them a control your team owns.
Tests run on pull requests and deployments, and block them when they fail. A suite nobody runs is documentation. A suite that stops a bad merge is a control.
We keep it green, triage failures and deal with flakiness while your team learns to own it. The engagement is designed to end with your engineers maintaining it, not with a dependency on us.
Coverage
Does each feature do what it is supposed to do, checked automatically on every change rather than by whoever has time before the release.
The things that already worked, re-checked so they keep working. This is where automation earns most of its money, because it is the work nobody wants to repeat by hand and nobody notices until it is skipped.
The contracts between your services, and between you and everyone you depend on. Faster and steadier to test than the interface, so most of the coverage belongs here rather than in a browser.
The handful of paths that actually matter — sign up, check out, submit, pay. Slow and brittle by nature, so they carry only the cases that genuinely need a whole system behind them.
How it behaves under the traffic you expect and the traffic you do not. Found in a test run rather than on the morning a campaign lands.
The same journeys on the browsers your visitors actually use, rather than the one the team happens to develop in.
Native and hybrid apps on real device profiles, where layout and input behave differently enough that desktop coverage does not transfer.
The tests wired into your pipeline with the authority to stop a merge or a deploy. A suite nobody runs is documentation; a gate is a control.
Repeatable data and an environment that resets cleanly. Unglamorous, and the thing that quietly stalls most automation projects.
Deliverables
Not a report saying the work happened. The work itself, in your source control, under your licence, readable by the engineers who have to live with it after we have gone.
Straight answer
There is no percentage on this page. That is deliberate.
Testing vendors advertise a number — some percentage reduction in testing time. We removed ours, because the honest version is that the figure depends entirely on your codebase, your release cadence and what you do today. Anyone quoting one before reading a line of your code is quoting somebody else’s project.
What we will do instead is measure your baseline during the assessment — how long a regression pass takes now, how many defects reach production, how often a release slips — then report the change against your own starting point. That number means something, because it is yours.
Behind the service
Test automation is not a side offering here. It is built into two products in our own software suite, and the engineers who build those are the ones who work on your suite.
Our AI-assisted development platform automates development and end-to-end testing together, so tests are written alongside the code rather than retrofitted once the deadline has already passed.
Our QA and security platform covers automated end-to-end and API testing, security testing, vulnerability scanning and compliance analysis. Coming soon — and the practice on this page is where it comes from.
Web and end-to-end
Selenium · Cypress · Playwright
Test frameworks
JUnit · TestNG
Mobile
Appium
Performance and load
JMeter
Before you ask
No — and a vendor who tells you otherwise is selling headcount reduction, not quality. Automation repeats a known check quickly and is hopeless at noticing what nobody thought to look for. This takes the repetition off your testers so they can do the second kind of work, which is why you hired them.
That is usually an argument for automation rather than against it — the faster a product moves, the more often something quietly breaks behind you. It does change what we automate. Fast-moving interfaces get the lightest cover; stable APIs and business-critical flows get the most, because those are the tests still earning their keep in six months.
Your team — which is why the runbook and handover are part of the work rather than a closing formality. Until that transfer is done, we do. If you would rather we kept operating the suite long term, that is a different engagement and we will say so plainly rather than let it drift.
Flaky tests are worse than no tests, because a suite people have learned to ignore still costs money and now gives false confidence too. Triaging them is part of operating the suite, not something we get to once it is bad enough to notice.
A scoped pilot on one business-critical flow — checkout, sign-up, whatever hurts most when it breaks. You get a working suite for that flow running in your pipeline, and a clear view of what the same approach looks like across the rest of the product before committing further.
We look at how you release, where defects escape and what your baseline actually is — then tell you what is worth automating and what is not. If the answer is “less than you think”, you will hear that too.
Related white papers and articles for Test Automation will appear here as they're published.
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