Engineer confidence into every release.
Software quality, regulated software assurance and AI assurance engineered across the product lifecycle.
Organisations need to release software, AI and regulated systems faster without compromising quality, compliance or operational confidence.
We integrate risk-based assurance, testing, automation and evidence generation across the product lifecycle.
Reliable, production-ready systems supported by traceable evidence and sustainable quality practices.
Five service areas, engaged on their own or embedded in delivery.
Regulated Assurance
Risk-based assurance for regulated software and digital systems, with evidence proportionate to intended use and patient, product or quality risk.
- Assurance strategy and planning
- Intended-use assessment
- Regulatory impact assessment
- Requirements and risk assessment
- Risk-based and scenario-based testing
- Traceability
- Assurance summary reporting
- Periodic review
- Change-control assurance
- Supplier and cloud-platform assessment
Software Testing
End-to-end testing that verifies whether software behaves correctly across user journeys, business processes, integrations and supported environments.
- Functional testing
- System testing
- Regression testing
- Integration testing
- API testing
- User-acceptance testing
- Exploratory testing
- Compatibility testing
- Mobile and web testing
Test Automation
Maintainable automation that improves release speed, repeatability and coverage without creating a fragile test-maintenance burden.
- UI automation
- API automation
- Regression automation
- Continuous integration testing
- Test-data strategy
- Automation framework design
- Automated evidence generation
- Quality gates
- Test reporting
Performance & Resilience
Production-readiness testing for systems that must remain responsive, stable and recoverable under real operational conditions.
- Load testing
- Stress testing
- Scalability testing
- Reliability testing
- Endurance testing
- Recovery testing
- Failover testing
- Capacity assessment
- Production-readiness review
AI & Data Assurance
Evaluation and assurance for AI-enabled systems, agents, models, retrieval pipelines and the data used to support them.
- AI system assurance
- Model evaluation
- Agent evaluation
- RAG evaluation
- Groundedness assessment
- Hallucination testing
- Robustness testing
- Human-in-the-loop control testing
- Data-quality assessment
- Data-integrity assessment
- AI regression evaluation
- Production monitoring strategy
Evidence generated as the system is built.
- 01RequirementsIntended use, defined and agreed
- 02RiskAssessed, so effort goes where risk is
- 03TestsRun automatically, on every build
- 04ApprovalsElectronic, attributable sign-off
- 05TraceabilityEvery requirement linked to its proof
Assurance Readiness Assessment
For quality and IT teams moving from document-heavy assurance to a risk-based approach.
- Review of your current assurance approach on representative systems
- Risk-based assurance framework and working templates
- Prioritised transition roadmap
- 01Technology Strategy
- 02Product Engineering
- 03Applied AI
- 04Connected Systems
- 05 · You are hereQuality Engineering
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