Path-derived end-to-end coverage
Suites generated from real user journeys and analytics, so coverage follows what matters rather than what was easy to write.
Once a red build is assumed to be flake, the suite has become a slow, expensive way of producing no information, and the real bug it caught ships anyway, because someone hit re-run.
Anees
Full Stack Developer · leads this service
We derive coverage from the paths users really take, treat flake as a defect rather than weather, and deliver failures with a reproduction attached so triage becomes a decision instead of an investigation.
Scoped per engagement. We start with whichever of these removes the biggest constraint first.
Suites generated from real user journeys and analytics, so coverage follows what matters rather than what was easy to write.
Non-deterministic tests are identified and pulled out of the signal path instead of being retried until green.
Layout and rendering are checked as deliberately as behaviour, because that is where silent breakage lives.
Schema and contract verification between services, so an integration break surfaces before a customer finds it.
Each failure arrives with a reproduction, a diff and a first guess at the change that caused it.
Parallelised runs, sharding, and a dashboard that shows trend rather than a single red or green light.
Typical shape for this service. Timings move with scope, the order does not.
Week 1
We measure current coverage and, separately, current trust: how often a red build is actually believed.
Week 1–3
Existing flake is fixed or quarantined first. Adding tests to an untrusted suite only makes it worse.
Week 3–8
Coverage grows along paths ranked by traffic and blast radius, not file by file.
Ongoing
The suite, the CI wiring and a policy for what happens when something goes red.
Chosen per engagement and biased toward what your team can maintain after we leave.
No. We build the automation layer so manual QA moves to exploratory testing, which is where people are far better than scripts.
Usually, through parallelisation, sharding and removing tests that duplicate coverage. We measure before promising a number.
Playwright and Cypress on the front end, pytest, Jest and Vitest underneath. We adopt what you already run where it is sound.
The most useful first message describes what someone on your team does by hand today and how often. That is enough for us to tell you whether it is worth building.