Practitioner articles
Detailed explanations, worked reasoning, and practical guidance for software validation and assurance decisions.
28 resources in All
AI Assurance
A field-ready method for deciding whether an AI-enabled GxP workflow is fit for release—without mistaking model accuracy, vendor claims, or human review for a complete validation rationale.
Supplier & SaaS
A release-aware assurance model for regulated SaaS: control the decision boundary, not an imaginary frozen build.
CSV & CSA
Vendor evidence can reduce duplicate effort, but only after the customer establishes relevance, credibility, and the remaining evidence gap.
Testing
A disciplined comparison of scripted, unscripted, and hybrid evidence—plus a practical charter for high-risk workflow testing.
Testing
A team reduces its test-script count from 120 to 45 and describes the result as a successful CSA transformation. That number tells us something about the work product, but very little about confidence in the system.
Testing
A screenshot can show a displayed value, message, or state. It usually cannot establish everything about the transaction that produced it. When a test concerns an interface, a screenshot of a green status may omit the source identity, transformation, receiving record, and retry behavior.
AI Assurance
An assistant produces a list of protocol findings in seconds. The reviewer finishes faster. That looks promising, but time alone does not establish whether the review improved.
Supplier & SaaS
Commercial software can arrive with extensive supplier documentation. That documentation can reduce uncertainty and support efficient assurance, but its relevance depends on what the organization is trying to establish.
Foundation · Video and chapter
Identify everything that can influence the AI-assisted outcome. A model is one component. A different document parser can drop a table; a retrieval filter can select an obsolete procedure; a reviewer can accept an unsupported answer; an integration can save it to the wrong record.