01How We Work / Quality & Delivery
Quality is howwe deploy.
A system that works in a demo and fails in operations is not a deployment.
We treat quality as two disciplines: QA for the system, and evaluation for the intelligence within it. Both are defined before build, tested throughout delivery, and carried into production.
02Two disciplines
Two disciplines.One quality standard.
- 01
QA & System Quality
Does the system work as intended?
Functional behaviour, integration, regression, reliability and real-world user acceptance, checked throughout the release lifecycle.
Our QA capability combines release testing, engineering-led test automation, and customer involvement so that quality is checked from multiple perspectives.
- QA
- Release testing
- SDET
- Customer HITL
- 02
AI Evaluation & Benchmarking
Does the intelligence perform to the standard that matters?
We define what good looks like for the AI before relying on it in production, establishing benchmarks, evaluation criteria and representative cases against which agentic systems can be measured.
Where the right cases do not yet exist, we build and curate them, including synthetic data where appropriate.
- Evaluation
- Benchmarking
- Data curation
- Agentic performance
03The release pipeline
No gate, no release.
Every release passes defined quality gates. Each has an owner, and the results are shared with you, including what failed.
- 01acceptance criteriaagreedagreed with the client owner
- 02builddonecompile · package · configure
- 03qa validationpassfunctional · integration · system behaviour
- 04ai evaluationreviewedbenchmarks · real cases · edge cases
- 05regressionpassevery release · every change
- 06reliabilitypassload · failure · recovery
- 07user acceptancesigned offreal workflows · real users
- 08staged rolloutdeployedpilot → wider release · rollback ready
- 09monitoring & evaluation● liveperformance · drift · adoption · owner
04What sits behind the gates
Quality is not one person or one test.
| QA & System Quality | AI Evaluation & Benchmarking | |
|---|---|---|
| Core question | Does the system work? | Does the intelligence perform? |
| Focus | Functionality, integration, regression, reliability | Accuracy, behaviour, edge cases, agent performance |
| Human input | Customer workflows and user acceptance | Expert review and human-in-the-loop evaluation |
| Automation | Automated testing and release validation | Repeatable evaluation sets and benchmark runs |
| Data | Test cases and production scenarios | Curated and synthetic evaluation data |
| Output | Release confidence | Measured AI performance against a defined standard |
05Evidence
Quality you can inspect.
| What a quality promise says | What our QA & evaluation produces |
|---|---|
| “Enterprise-grade” | Written acceptance criteria, agreed and signed off |
| “Rigorously tested” | Test results, defects and release evidence |
| “Reliable AI” | Evaluation sets, benchmarks and model-performance results |
| “Accurate AI” | Measured performance against your real cases and defined thresholds |
| “Seamless launch” | A staged rollout plan with checkpoints and rollback paths |
| “Ongoing support” | Production monitoring, evaluation, a named owner and agreed response process |
06Principles
How we think about quality.
- 01Quality is planned, not inspected in.Test and evaluation plans are part of the design, not a phase at the end.
- 02Independent checks where they matter.Quality checks should not depend solely on the people who built the system. Where appropriate, validation is separated from delivery, with customer and human-in-the-loop review providing another layer of scrutiny.
- 03Measure behaviour, not demos.We test how the system behaves in the real environment, with representative data, real workflows and real users.
- 04Say what it can’t do.Known limitations, failure modes and evaluation results are documented and shared before release, not discovered after.
07The standard
Built to be tested.Deployed with evidence.
Quality isn’t a promise we make after the work is done.
It is part of how we build, evaluate, release and operate every solution.
08Start a conversation
Need it to work in production, not just in a demo?
Tell us about the problem, the outcome you need and the team you have. We’ll help you work out what to build, who should build it and how to put it to work.