Quality Assurance & Testing
Release on a Friday without holding your breath.
We set up a test strategy that matches your risk: fast unit and API tests where logic lives, a thin layer of end-to-end tests on the journeys that make money, and exploratory testing for what scripts miss. All of it runs in CI on every change.
Schedule 1
What is included
- A-4.1
Test strategy
What to test, at what layer and how often, written down and agreed with your team.
- A-4.2
End-to-end automation
Playwright or Appium suites on critical journeys, stable enough that a red build means a real bug.
- A-4.3
API and contract tests
Every endpoint checked for shape, errors and permissions, including the ones that should say no.
- A-4.4
Performance and load testing
Find the breaking point in staging, not on launch day.
- A-4.5
Exploratory and accessibility QA
Experienced testers who think like users, and like attackers.
Schedule 2
Typical projects
- Adding automation to a product with only manual testing
- Pre-launch quality gates
- Regression suites for a legacy system before refactoring
- Load testing ahead of a marketing push
Materials
- Playwright
- Cypress
- Appium
- Vitest
- pytest
- k6
- Postman
- GitHub Actions
Schedule 3
How it runs
- 01
Discovery · 1–2 weeks
We map the problem, the users, the data and the constraints, and agree what success will be measured by.
- 02
Blueprint · end of discovery
Architecture, scope, milestones and a fixed price for the first build phase, all in writing. You can stop here and keep the blueprint.
- 03
Build · weekly demos
Short iterations with a working demo each week, automated tests from day one and a shared board you can always see.
- 04
Launch & handover · planned cut-over
Staged rollout, monitoring switched on, documentation and a recorded handover session with your team.
- 05
Run & improve · optional
A monthly support plan, or nothing: the handover is written so that you never need us to keep the lights on.
Schedule 4
Common questions
Do you test software you did not build?
Yes. Many QA engagements start with an existing product and team; we fit into your pipeline and tooling.
How do you avoid flaky end-to-end tests?
Fewer, better ones: stable selectors, seeded test data, network control and a rule that a flaky test is fixed or deleted the same week.