Software Testing & QA
Manual & Automated Testing
Most teams do not have a testing problem. They have a 'we test the happy path and ship' problem. Defects surface in production, get patched under pressure, and the patch introduces the next one. We test the paths people actually take, at the volumes you actually run, and we tell you what we found rather than quietly marking a ticket green.
The Challenge & The Orus Solution
We turn complex business challenges into resilient, scalable digital systems.
The problem
Testing is the first thing cut when a deadline moves, and the cost of cutting it never shows up on the same sprint that saved the time. It shows up two months later as a production incident, a corrupted report, or a customer who found something your team never thought to try.
The usual symptoms are recognisable: a QA process that exists only as a developer clicking through their own feature, no idea what happens at ten times current load until it happens, and a release where nobody can say with confidence what was tested.
- Defects reach production and are found by customers rather than by you
- Nobody can say what was tested before a release, or what was not
- Performance is unknown until real volume arrives and it is too late
- The same bug returns because nothing stopped it coming back
- Manual regression takes days, so it gets skipped when it matters most
Our solution
We start by writing down what the software is actually supposed to do — which, on most projects we inherit, has never been written down. From that we build a regression suite that runs automatically on every change, so a fixed bug stays fixed.
Automation covers the repetitive paths. Humans cover the parts where judgement matters: whether an error message makes sense, whether a workflow is usable under pressure, whether the numbers on a report are actually right. We do not pretend automation replaces that.
- A test plan derived from real usage, not from a feature list
- Automated regression running on every commit
- Exploratory testing by people, on the parts that need judgement
- Performance tested at your real data volumes, not a hundred sample rows
- A defect report that distinguishes 'must fix' from 'noted'
Why businesses choose Orus Studio for QA
QA is worth paying for only if it can deliver bad news. We structure the engagement so it can.
We report what we found
A test report that says everything passed is usually a report that did not look hard enough. Ours lists what is broken, what is risky, and what we chose not to test.
We test at your volume
Performance problems appear at scale and nowhere else. We generate realistic data volumes rather than testing against a demo dataset.
Automation you own
Test suites live in your repository, in mainstream tools, so your own team can run and extend them.
We will say the release is not ready
That is the entire point of an independent QA function, and it is the part most vendors quietly skip.
Who this is for
QA engagements work best where the cost of a defect is real and measurable.
- Teams shipping to production without an independent test pass
- Products where a defect has financial, clinical or regulatory consequences
- Companies whose manual regression now takes longer than the sprint
- Businesses preparing for a scale event — a campaign, a season, a launch
- Teams inheriting a codebase with no test coverage and no documentation
What you get
- A written test plan and acceptance criteria
- An automated regression suite in your repository
- Performance benchmarks at agreed concurrency levels
- A prioritised defect report, severity-rated
- A security review against the OWASP Top 10
- CI integration so tests run without anyone remembering to
What we build and deliver
Testing services scoped to where your risk actually sits — What we build:
- Functional testing — Every user journey verified against agreed acceptance criteria, including the unhappy paths where software usually disappoints.
- Automated regression suites — Playwright or Cypress for web, Appium for mobile, wired into CI so a passing build means something.
- API and integration testing — Contract tests against every endpoint, including the failure modes third-party services actually produce.
- Performance and load testing — k6 or JMeter at realistic concurrency, with the bottleneck identified rather than just the number reported.
- Security testing — OWASP Top 10 review covering authentication, authorisation, injection and data exposure before launch.
- Compatibility testing — Real devices and browsers your analytics show your users on, not a generic matrix.
- Accessibility testing — WCAG 2.2 AA checks, which also matter for public-sector and enterprise procurement.
- Test data management — Anonymised production-shaped data, because testing against a hundred clean rows proves nothing.
Frequently Asked Questions
Transparent answers about timelines, scope, technology stacks, and our process.
Do we need automated testing, or is manual enough?
Can you test software you did not build?
How long does a QA engagement take?
What happens if you find a lot of defects?
Shipping without an independent test pass?
Tell us what you are releasing and we will tell you honestly where the risk sits — and whether you need a full QA engagement or just a focused pass.