46%
of developers actively distrust the accuracy of AI-generated code — while 84% use it or plan to.
Independent software quality engineering
Your team ships more code than anyone has verified.
AI coding tools made your engineers faster. They did not make your release safer, and most teams have no measurement of the difference. We find out what changed, and we put our name on the answer.
Published evidence
56%
of AI-generated code passes a security review. Cross-site scripting passes 15% of the time.
19%
slower. Experienced developers in a randomised controlled trial using AI tools — while believing they had been 20% faster.
None of this is an argument against using AI. It is an argument that the verification layer which used to be implicit now has to be deliberate — and that somebody has to be accountable for it.
What we do
Three fixed-scope engagements. No hourly billing, no open-ended retainers, no discovery phase that bills you for learning your codebase. Every price is quoted before any work starts.
AI Code Assurance Diagnostic
Two weeksFixed fee
Find out what AI adoption actually did to your defect profile, test coverage and security posture.
Deliverables
- Findings report
- Risk-ranked remediation roadmap
- 90-minute walkthrough with your engineering leadership
CI/CD Quality Gate Build
Four to six weeksFixed fee
Build the gates that stop the problems the diagnostic found.
Deliverables
- Pipeline quality gates
- Test tiering
- Flake control
- Coverage policy
- Handover documentation
Release Readiness Retainer
MonthlyOngoing
Ongoing ownership of the quality gate, so it does not decay the month after we leave.
Deliverables
- Continuous gate ownership
- Release sign-off
- Monthly quality report
How we test
Three disciplines, and what we actually write in. Each is set out in full on the testing page, including what it cannot do. If you want one on its own rather than inside a diagnostic, that is a normal thing to ask for.
Manual and exploratory testing
- Exploratory charters
- Risk-based session testing
- Accessibility review
Test automation
- Playwright
- Selenium WebDriver
- TypeScript
- Java
- Python
- CI pipelines
GenAI for QA — agents built and deployed
- Agent design
- Tool and API integration
- Evaluation harnesses
- CI deployment
Questions we get asked
We already have a QA team. What is this?
Then you have people who know your product, and probably no measurement of what AI-assisted development changed. This is a second set of eyes with a method, not a replacement for your team.
Why not just use an AI testing tool?
Use one. Tools generate tests; they do not tell you whether the tests are testing the right things, and they cannot take an accountable position on a release. That is the part we sell.
How is this different from an offshore QA vendor at a third of the price?
It mostly is not, if you want scripted regression executed cheaply — hire them for that. It is very different if you want somebody to look at your architecture, tell you what is actually at risk, and sign their name to it.
You build QA agents and you sell human verification. Isn't that a contradiction?
No, and the distinction is the whole business. We build and deploy GenAI agents for QA, and we use them in our own delivery for first-pass analysis, test generation and triage — an agent widens the search enormously. What an agent cannot do is take an accountable position on your release. Every finding that reaches your report is verified by one of our engineers before it leaves. We will not sell you AI-generated assurance of AI-generated code.
Do you do manual testing, or only automation?
Both, and we will tell you which one your problem needs. Exploratory and manual testing finds the classes automation is blind to — broken workflows, confusing states, accessibility failures a scanner scores as passing. Automation holds the line on regression once you know what to hold. Selling you one when you need the other is how QA budgets get wasted.
What happens after I send an enquiry?
We read it and reply from a person, usually within one business day. We will want to know what tooling you adopted and roughly when, your engineer-to-QA ratio, and what went wrong most recently — the form asks all three, so answering there means the first reply can be useful rather than a request for more information. If the diagnostic is not right for you, that reply will say so.
Where are you based?
Richmond, Virginia. Most work is remote; we can be on site in the Richmond–DC corridor.
Tell us what is breaking.
Tell us what you adopted and what has broken since. If we cannot help, we will say so.