Traceability
Designing an evidence chain that survives audit
The goal is not “more documents”—it’s a coherent narrative. A good evidence chain makes it easy to answer:
what changed, why it changed, which risks are affected, and what evidence supports acceptance.
Practical checks:
• Each requirement has acceptance criteria and a verification method.
• Each risk control is explicit: where it lives (design/process) and how it is verified.
• Release evidence can be assembled by following links, not by searching inboxes.
Related: Regulated Delivery Approach
DevSecOps
CI/CD that generates evidence, not just builds
In regulated environments, pipeline outputs must be defensible: controlled builds, test evidence capture,
and quality gates that reflect risk and intended use.
Practical checks:
• Build provenance is repeatable and reviewable.
• Automated tests produce evidence artefacts suitable for review.
• Security checks are risk-informed and integrated into release readiness.
Optional: DevSecOps Accelerator (Regulated
Software)
Healthcare AI
Pragmatic guardrails for AI/ML in regulated workflows
AI/ML introduces uncertainty. Good governance makes behaviours testable, boundaries explicit, and
responsibilities clear.
Practical checks:
• Intended use and system boundaries are unambiguous.
• Validation expectations are defined early, aligned to risk controls.
• Monitoring and change control expectations are defined for the deployed context.
Related: AI/ML Integration Services
Free Resource
Evidence Chain Readiness Checklist
A practical one-page self-assessment to evaluate your traceability, risk control mapping, and release
evidence posture—before an auditor does.
What's included:
• Requirements ↔ Risk ↔ Tests mapping questions
• Release evidence assembly check
• Pipeline evidence hygiene indicators
• Scoring guide with interpretation
Download
Checklist
