Coverage that tracks the requirements. Not someone's memory of them.
We use AI to make quality engineering keep pace with AI-speed development. SpurTree QA engineers generate test cases in bulk from each requirement's acceptance criteria, scaffold them into automation scripts and track coverage on a live dashboard in ADIS. Gaps show up the moment they open, and every test links back to the requirement it proves.
You're in the right place if…
- Teams whose test suites lag behind the features being shipped
- Products where manual regression testing is slowing releases
- Engineering leaders who cannot say which requirements are actually covered by tests
- Teams adopting AI coding tools that need quality checks to keep up
What gets in the way.
Tests written from memory
Test cases are drafted from what people remember of the spec, so coverage drifts from the requirements.
Test cases that never become automation
Cases sit in spreadsheets or prose and are run by hand, if at all.
Gaps found after release
Without a live view of coverage, missing tests are discovered when something breaks in production.
AI Quality Engineering, end to end.
Test case generation
Whole suites of test cases generated directly from acceptance criteria, reviewed by our QA engineers.
Automation scaffolding
Generated cases are scaffolded into runnable automation scripts rather than left as documentation.
Quality metrics dashboard
A live view of pass rates, coverage and gaps across the suite, so you can see release readiness.
Requirement-to-test traceability
Each test links to the requirement it covers in the ADIS traceability grid, alongside design, code and security evidence.
Verification before review
Changes pass compile verification, static analysis, secrets scanning and smoke tests in an isolated environment before reaching a reviewer.
A delivery approach you can plan around.
Assess current coverage
We review your existing tests, requirements and release process to see where quality risk sits.
Tighten acceptance criteria
We make sure requirements carry clear acceptance criteria, since generated tests are only as good as the spec.
Generate and automate
We generate test cases, scaffold automation and wire suites into the delivery pipeline.
Monitor and close gaps
We track coverage on the dashboard and close gaps as new requirements arrive.
Ways to work with us.
QA within a spurtree POD
Quality engineering delivered as part of a full-lifecycle POD running your roadmap.
Focused QA engagement
A scoped engagement to build out generated, automated coverage for an existing product.
Technologies we work with
- ADIS
AI Quality Engineering: common questions.
Do AI-generated tests replace QA engineers?
No. AI generates and scaffolds the tests; our QA engineers review them, decide what matters and keep the suite honest. The aim is broader coverage, not fewer people checking it.
Where do the test cases come from?
From each requirement's acceptance criteria. That keeps coverage mapped to the spec, which is why we also help sharpen acceptance criteria where they are vague.
Can you work with our existing test suite?
Yes. We start by assessing what you have, then add generated coverage where it is thin rather than starting from scratch.
Let's talk about your ai quality engineering needs.
We'll reply within one business day to understand the skills and engagement you need and propose a POD shape.