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We make sure your software works flawlessly — with functional, automated, performance and security testing across every device and browser.
Bugs cost trust and revenue. Our QA team catches issues before your users do — with thorough manual and automated testing across the full experience.
From functional and API testing to performance, security and cross-device checks, we deliver detailed bug reports and a product that's truly ready for release.
A complete set of solutions delivered by a team that sweats the details.
Verify every feature works exactly as intended.
Human-driven testing that catches real-world issues.
Fast, repeatable test suites for continuous quality.
Validate endpoints for correctness, speed and security.
Test across Android and iOS devices and versions.
Cross-browser checks for a consistent experience.
Load and stress testing to ensure speed at scale.
Find and fix vulnerabilities before attackers do.
Clear, reproducible reports that speed up fixes.
A proven, transparent process from first idea to launch and beyond.
We map your goals, users and scope to define a clear, actionable roadmap.
Wireframes and interactive prototypes validate the experience before we build.
Agile sprints turn the design into clean, tested and production-ready code.
Functional, performance and security testing on real devices and browsers.
Smooth release to your servers, app stores or the cloud with zero downtime.
Ongoing monitoring, updates and enhancements keep everything running.
We've delivered results across a wide range of sectors and business sizes.
Experienced people, secure solutions and a commitment to doing it right.
Senior engineers and designers with years of hands-on delivery across industries.
Security best practices, encrypted data and role-based access baked into every build.
Clean, modular architecture that grows painlessly as your business scales.
Transparent milestones and agile sprints keep your project on schedule.
Regular demos, shared boards and a single point of contact from day one.
Post-launch maintenance and support plans so you are never left stranded.
Testing is not a phase at the end of a Gantt chart. It is a set of habits, a device matrix and an agreed definition of what counts as broken.
Developers test their own work, and they test it the way they built it — along the path they had in mind. That catches the obvious break and misses the interesting one, because you cannot easily imagine the assumption you did not know you were making.
So on our projects QA is held by someone who did not write the code. Not necessarily a large team — on a small build it is one person part-time — but a different person, with a mandate to try the things nobody planned for: submitting the form twice, entering a date in the past, uploading a 40MB photo, losing connection mid-payment, using the browser back button after checkout.
QA compressed into the final week of a twelve-week project is not quality assurance. It is bug discovery with no time left to fix anything — and worse, the bugs found then are the expensive kind, rooted in decisions made in week two.
We test as features land. Each feature gets checked when it is built, while the developer still has it in their head and while a design change is still cheap. Then a regression pass before each release covers the paths that must never break. The result is fewer bugs found late, and the ones found late are shallow.
Automating everything is a common and expensive mistake: a large end-to-end suite that breaks whenever a button moves, takes an hour to run, and gets switched off within two months because nobody trusts it.
Our split is pragmatic. Automate the business rules where being wrong costs money — tax and discount calculations, permission checks, approval thresholds, invoice numbering, stock movements — because these are cheap to test, stable, and catastrophic to get wrong. Automate a small number of critical end-to-end journeys: sign up, log in, place an order, make a payment. Do not automate exploratory testing, visual judgement, or flows that are still changing weekly; a human is better and cheaper at those until the design settles.
We do not chase a coverage percentage. Coverage measures which lines ran, not whether the behaviour is correct, and teams optimising for the number end up testing getters.
The matrix should come from your analytics, not from a template. In practice, for most clients in this region it means the current and previous versions of Chrome and Safari, Firefox and Edge on desktop, Safari on iOS — where a good share of iOS users are on older major versions — and Chrome on Android across a range of manufacturer skins.
Critically, at least one real mid-range Android phone with limited RAM, crowded storage and a throttled connection. That single device surfaces more genuine problems than any simulator: oversized images, lists that rebuild on scroll, slow cold start, and forms where the keyboard hides the submit button. We keep a small set of real devices and use them before every release.
"Critical" means different things to a client and a development team, which is why we define it in writing at kickoff rather than during a tense release call:
| Level | Definition | Response |
|---|---|---|
| Critical | Data loss, security exposure, payments broken, system unusable | Stop and fix now; blocks release |
| High | A main journey is broken with no workaround | Fix before release |
| Medium | Broken but with a workaround, or affects a secondary flow | Scheduled; may ship |
| Low | Cosmetic, wording, minor alignment | Batched into a later release |
With that agreed, "can we go live?" becomes a factual question rather than a negotiation.
Good testing needs awkward data: a customer with no orders, an order with fifty line items, a name with an apostrophe, an address in Urdu, a 2MB product photo, an expired card, a zero-value invoice. We build a seeded set covering these so every tester works from the same starting point and results are reproducible.
What we do not do is test against a live copy of customer data. If production data is needed for realistic volume, it is anonymised first — names, emails and phone numbers replaced — because a staging environment with real customer records is a data breach waiting for a misconfiguration. Real email addresses in a test database are also how a test run accidentally sends four hundred people an invoice.
Full penetration testing and formal load testing are separate engagements and not what most projects need. What every project does get from us: the 24-point performance pass before launch, measured on a throttled mobile connection rather than on office fibre; a load check against the realistic peak you have described, because "400 concurrent users during registration week" is a number worth verifying rather than hoping about; a dependency vulnerability scan in the build pipeline; and a run through the common web vulnerability classes — injection, broken access control, insecure file upload, secrets in the repository, missing rate limits on login.
Before anything goes live we confirm: the regression suite passes; the critical journeys have been walked manually on a real phone; a database backup has been taken and a restore has been tested; migrations have been run against a copy of production data first; error tracking and monitoring are live and receiving events; a rollback path exists and has been exercised; and the third-party integrations have each made one real call in the production configuration. It is a boring list. Boring lists are what make releases uneventful.
