Testing is bought after a bad release and forgotten after two good ones. The useful framing is not 'do we have bugs' — everyone does — but 'how long between a bug being introduced and someone finding it'. Days is manageable. Discovering it from a customer is not.
QA and test automation covers manual exploratory testing, automated end-to-end suites running in CI, cross-browser and device coverage, and regression testing before each release. The aim is to shorten the time between a defect being written and being caught, not to eliminate defects.
The critical-path suite runs on every commit. A slow suite is a suite people learn to bypass.
The twenty journeys that carry the business. Everything else is manual until it earns automation.
A test that fails randomly teaches the team to ignore red builds, which is worse than having no test.
Low, mid and high-end Android plus iOS — because your users are not all on the newest phone.
Test strategy document
Critical path suite in the pipeline
Full regression suite
Test reports per release
A suite the team trusts
The same defect, fixed in March and back in July, because nothing captured it as a test. Without a regression suite every fix is temporary and every release is a fresh negotiation with luck.
The cost of a defect varies enormously by context, and so should the investment in catching it.
A checkout bug on a sale day, discovered from a drop in orders rather than an alert.
Automated purchase journeys, prepaid and COD, run before every release and on a schedule against production.
Calculation and eligibility errors that are compliance incidents rather than bugs.
Unit-tested rules with worked examples, plus end-to-end tests over the full application journey.
A regression affecting one tenant's configuration, found weeks later by that tenant.
Test data covering the configuration matrix, and cross-tenant isolation tested automatically.
Data accuracy and access control failures with consequences well beyond a support ticket.
Permission tests per role, audit trail verification and accessibility testing as a requirement rather than a nicety.
A crash on one OS version discovered through store reviews and a rating that takes months to recover.
Device-matrix testing, crash reporting with alerting, and staged rollout so a bad release reaches five percent, not everyone.
A codebase nobody wrote, where every change risks breaking something invisible.
Characterisation tests around current behaviour first, which makes the code safe to change at all.
Automation is not about replacing testers. It is about freeing them from repeating the same twenty clicks so they can do the exploratory testing that actually finds interesting bugs.
Login, checkout, payment, the main workflow — the journeys that run before every release and must never break. These earn their maintenance cost within weeks.
Screens still changing weekly cost more in test maintenance than they return. Wait until the design settles, then automate.
Automated tests confirm what you thought to check. A human using the product badly, on purpose, finds the things nobody thought of — and that is where the serious bugs live.
Once a suite fails randomly, the team stops trusting red. Fix or delete flaky tests immediately; tolerating them destroys the value of everything else in the suite.
What gets automated, what stays manual, what runs per commit versus nightly — written down, so testing is a plan rather than a habit.
The twenty journeys that carry the business, automated in Playwright and running in CI.
Contract and behaviour tests on your endpoints, which are faster and far more stable than driving the same logic through a browser.
Chrome, Safari and Firefox, plus a real Android device matrix across three price tiers.
Every fixed bug becomes a test, which is the only mechanism that stops the same defect shipping twice.
Automated checks in CI plus manual keyboard and screen-reader passes on the key journeys.
For sale days and campaign launches: find the breaking point deliberately, in advance, rather than discovering it live.
One tracker, severity definitions everyone agrees on, and a weekly triage — so the log shrinks instead of accumulating.
Testing gets bought after a bad release and forgotten after two good ones. The useful framing is not whether you have bugs — everyone does — but how long passes between a defect being written and someone finding it.
Manual exploratory testing, automated end-to-end suites running in CI, cross-browser and real-device coverage, API-level tests and a regression suite that grows with every bug fixed. The aim is to shorten the discovery window, not to eliminate defects, which is not a thing anyone achieves.
Not a coverage percentage — that target rewards testing trivial code. Start with the journeys the business cannot function without: signup, login, checkout, payment, the core workflow. Then the paths you have broken before. Then API-level tests, which give more stability per hour of effort than driving the same logic through a browser. The full order is in test automation strategy.
For Indian products that means a real device matrix across three price tiers, not emulators alone. A product that feels fine on a flagship and stutters on a two-year-old mid-range Android is a product with a rating problem it does not know about yet.
A common engagement: a system that works, no tests, and nobody willing to change anything. The route in is characterisation tests that describe what the system currently does — right or wrong — which is what makes unfamiliar code safe to modify at all. That work usually runs alongside maintenance or a modernisation programme.
Every stage ends in something you can hold — a document, a build, a live account. If a stage cannot name its output, it is a meeting, not a stage.
Review the product, the current release process and the last three incidents to find where defects are actually escaping.
Automate the journeys the business cannot afford to break, and get them running in CI.
API tests, cross-browser, device matrix, and accessibility checks added incrementally.
Manual sessions per release, with findings written up and prioritised rather than mentioned in a call.
Suite kept green, flaky tests fixed or deleted, and every new bug converted into a test.
Everything here is part of the engagement at no extra cost. We do not itemise them on an invoice and we do not withhold them if you leave.
What gets automated, what stays manual, what runs per commit versus nightly. Yours to keep and to hand to whoever builds next.
Every defect we fix arrives with a test that would have caught it, so the same regression cannot ship twice.
A written record of what was tested and what was found before each release, rather than a verbal all-clear.
We do not hand over a suite the team has learned to ignore. A red build has to mean something.
Automated checks plus a manual keyboard pass on the key journeys, included rather than treated as a separate audit.
Longer answers to the questions people ask before they hire anyone for qa & test automation.
Built by us, free, no signup, nothing uploaded to a server. Take them whether or not you ever become a client.
It scales with how much has to be covered and how often you release: a one-off strategy and critical-path automation is a fixed project, while ongoing QA alongside development is a monthly engagement. Pre-launch assurance for a sale event or major release is scoped separately. We quote after looking at the product and your release process.
Tell us what you have now and what you are trying to reach. We will audit it and tell you what we would do, what it would cost and whether you need us at all. The audit is free and yours to keep.