Test Architecture & QA Platform Engineering

Your regression suite runs overnight, and the failures nobody trusts outnumber the ones that matter. Adding tests makes it worse. Adding people makes it worse more slowly.

That's not a testing problem. It's an architecture problem, and no amount of additional test cases will fix it.

Fixed-scope engagements that rebuild how your tests are structured, where your test data comes from, and how your pipeline runs them.

Schedule an Engineering Call Take the QA maturity check

Why is my test suite so slow?

Slow suites are a symptom. So are flaky ones. The underlying cause is almost always structural, and it shows up in recognizable ways:

The suite gets slower every sprint and nobody can say which tests are load-bearing.
Failures get re-run rather than investigated. Once a team stops believing a red build, the suite has stopped doing its job even when it passes.
Tests can only run one at a time, because they share test data and step on each other.
A new engineer takes weeks to add a test — the framework has accumulated conventions nobody wrote down.
Most coverage sits in the UI layer, not because those journeys matter most, but because that's where the framework made it easy.
Nobody will delete a test, because nobody can tell what it covers.

If three or more of those are true, more tests will make the situation worse, not better.

What we do

Three workstreams. Most engagements need one of them badly and the other two partially.

Framework architectureRebuilding a suite, or migrating one — Selenium to Playwright, or an in-house framework nobody maintains any more. The decision that matters isn't the tool. It's what belongs at each layer.Most suites are top-heavy: coverage sits in the browser because that's where the original framework made writing tests easy. Moving that coverage down — into API, contract, and component tests — is what turns an overnight run into a coffee-break one. The browser tests that survive are the handful of journeys that genuinely need a browser.
Test data and environmentsShared, mutable test data is the single most common cause of flakiness we find. Tests pass alone and fail together, and teams learn to re-run rather than fix.We build provisioning that gives each run its own isolated data, seeded to a known state and torn down after. That's what makes parallel execution possible, and parallel execution is where most of the runtime reduction actually comes from.
CI/CD test orchestrationWhere tests run, when, in what order, and what they gate. Not everything belongs on every commit. A pipeline that runs the full suite on every push trains engineers to ignore it.We define the tiers — commit, merge, release — and wire quality gates that block for real reasons and only real reasons.

How it works

Fixed scope. Four to six weeks. Defined deliverables and a handover at the end.

What you get at the end is a working pattern and a route to follow, not a finished migration. A full migration of a mature suite takes months and it should be your team doing it — they're the ones who'll live with it. Our job is to make sure they're migrating toward something that holds up.

This engagement sits in the Platform layer of the AI-Native Delivery Framework. It's usually the prerequisite that makes the AI capability layer worth building.

Weeks	What happens
1	Assess the current suite — runtime, flake rate, layer distribution, data dependencies
2	Architecture decisions and the migration path, agreed with your team
3–5	Reference implementation: the new structure, working, on a real slice of your suite
5–6	Handover — documentation, conventions, and your engineers building on it

Tech Stack

We don't have a preferred framework we push onto every client. The right choice depends on what your engineers already know, what your application is built in, and what your CI can run. Migrating to a tool your team doesn't want to maintain is how suites get abandoned twice.

Browser
Playwright, Selenium, Cypress
API and contract
REST Assured, Pact, Postman/Newman, supertest
CI/CD
GitHub Actions, GitLab CI, Jenkins, Azure DevOps
Test management
TestRail, Zephyr, Jira, Confluence

What you get

Current-state assessment — runtime, flake rate, layer distribution, and where the time actually goes
Architecture decision record — what goes at each layer and why, written so it survives your next hire
Reference implementation — the new structure working against a real slice of your suite
Test data provisioning — isolated, seeded, repeatable
Pipeline configuration — tiered execution and quality gates
Migration plan — sequenced, with effort estimates your team can plan against
Handover sessions — your engineers building on it before we leave

The terms

Fixed scope, fixed price, four to six weeks. You know the cost before it starts and there's no open-ended engagement to exit.