Purpose, region, organisational role, intended users and affected people, sector, data use and decision impacts inform applicability.
THE PLATFORM / AI DELIVERY IN PRACTICE
Your AI-assisted work.
Validated through delivery.
Validate requirements, designs, code and QA artefacts your teams create with AI. Follow the assessment from project context to findings backed by the material examined, human review and reassessment.
One module, several, or all four. Your assessment keeps its scope visible.
FOUR PHASES. ONE ASSESSMENT-LED APPROACH.
Different questions.
The same need for proof.
Choose a phase to inspect its material, assessment focus and output. The example below reuses selected findings from the recorded fictional EU/UK recruitment project; saved phase results keep the material and recorded decision together.
REQUIREMENTS / PHASE CHECK
What needs to be defined?
Stories and requirements.
Duty gaps, conflicts and suggested acceptance criteria or test scenarios.
A route to request human intervention and challenge an automated work decision.
“Automatically reject applicants below score 60 with no human review.”
The requirement excludes human review.
The recorded assessment flagged a conflict with the relevant automated-decision safeguards.
Basis: recorded requirement · EU GDPR Art. 22; UK GDPR Arts. 22A–22C. EU AI Act Art. 14 is separately identified as future oversight readiness.
Scope: Suggested requirements, criteria and tests are proposals for human review. Selected findings from a recorded fictional assessment; simplified for explanation. Proposed corrections are not completed fixes. These excerpts are not an overall accuracy or legal-compliance result.
DESIGN / PHASE CHECK
How will the control work?
Architecture and design material.
Located passages, planned controls, gaps and unresolved questions.
A route to request human intervention and challenge an automated work decision.
“Automatically reject applicants below score 60 with no human review.”
The design does not describe the safeguards.
The examined design explicitly excludes human review and does not explain intervention or challenge handling.
Basis: design.md · EU GDPR Art. 22; UK GDPR Arts. 22A–22C. EU AI Act Art. 14 is separately identified as future oversight readiness.
Scope: A planned control in a design is not proof that the behaviour is implemented. Selected findings from a recorded fictional assessment; simplified for explanation. Proposed corrections are not completed fixes. These excerpts are not an overall accuracy or legal-compliance result.
BUILD / PHASE CHECK
What implementation material exists?
Supported code and configuration; configured scanner findings.
Supported AI touchpoints, source locations and mapped implementation material.
A route to request human intervention and challenge an automated work decision.
return {"reject": candidate["score"] < 60}
Review controls are not shown in the material.
The examined code returns automatic rejection. Supporting implementation material for review and challenge controls was not found in the material assessed.
Basis: app.py · EU GDPR Art. 22; UK GDPR Arts. 22A–22C. EU AI Act Art. 14 is separately identified as future oversight readiness.
Scope: Coverage depends on supported patterns, languages, frameworks and configured scanners; it is not exhaustive. Selected findings from a recorded fictional assessment; simplified for explanation. Proposed corrections are not completed fixes. These excerpts are not an overall accuracy or legal-compliance result.
QA / PHASE CHECK
What has actually been examined?
Test cases and scripts; configured screenshots, browser journeys or API conversations.
Relevant checks, retained observations and visible material gaps.
A route to request human intervention and challenge an automated work decision.
“Your application is rejected automatically. No human review or appeal is available.”
The sampled conversation refused review.
The retained API observation showed no available human-review or appeal route. This is a sampled finding, not proof about every possible interaction.
Basis: QA-HANDOVER transcript · EU GDPR Art. 22; UK GDPR Arts. 22A–22C. EU AI Act Art. 14 is separately identified as future oversight readiness.
Scope: Reviewing a script does not execute it. Browser/API observations are sampled and do not prove every behaviour. Selected findings from a recorded fictional assessment; simplified for explanation. Proposed corrections are not completed fixes. These excerpts are not an overall accuracy or legal-compliance result.
Independent or combined. Reports identify the phases actually assessed. A design review does not prove implementation; reading a test script does not execute it.
EXPLORE THE PROCESS
See what happens
at each step.
Select a step to follow the assessment journey. One project can use one, several or all four delivery modules.
Define the project and assessment scope.
Describe the AI use, regions, organisational roles and relevant facts. Select the phases to assess and any relevant organisational policies.
Project context and the phases selected for assessment.
Provide or connect the project material.
Upload or paste material, link supported documents, connect supported repositories and scanner findings, import supported test material, or configure a QA test target.
Selected material made available through the supported route and permissions.
Establish and review applicability.
Combine the project configuration with project material from the selected phase. Identify relevant configured obligations and flag missing facts or contradictions that could affect scope.
Scope questions for human confirmation, followed by re-evaluation of relevant configured obligations.
Examine the phase-appropriate material.
Run the selected module and review its findings alongside the material actually examined. Keep requirements, design, implementation and QA material distinguishable.
Findings, references, material gaps and uncertainty within the selected phase.
Review gaps and decide what to do.
Inspect the reference, material, finding and uncertainty. Record a decision against selected saved assessments and use findings to inform remediation and reassessment.
A recorded human decision with the selected saved results as its basis.
Revisit when relevant circumstances change.
Inspect monitored source changes and notices affecting earlier assessments. Rerun the checks needed for the next decision.
A new assessment where needed, while earlier records retain their original context.
Artefact analysis can reveal missing facts or contradictions. Review scope questions before treating a result as settled.
Distinguish current duties, future readiness, organisational policies and selected standards references.
HOW PROJECT MATERIAL ENTERS THE LAB
Connect the material.
Keep the scope.
Upload, link or connect. The selected phase decides what the Lab examines; only selected material is used, within configured permissions.
Upload or paste
Requirements, designs, code archives, QA cases and supporting documents.
Link document sources
Configured access to supported sources, including Confluence and SharePoint/OneDrive.
Repositories & scanners
Supported repository reads and configured GitHub code scanning or SonarQube findings.
Import or observe
Configured Jira/test-case reads, supported files, or a test application/API for sampled QA.
THE SELECTED PHASE SETS THE EXPECTED MATERIALS
- Stories
- Acceptance criteria
- Supporting requirements
- Repositories
ASK THE LAB
One conversation.
The whole Lab.
Anything DutAIx can do, you can ask for in conversation: create a project, add material, run the four checks, inspect saved results, compare versions and prepare the next action. Chat history keeps the work together, so you can return and continue where you left off.
The assistant follows the same review boundaries as the pages. Consequential actions still need the supported confirmation and human review.


SEE IT IN CONTEXT
Follow a finding.
Understand the decision.
Explore the platform using fictional project material in a practical walkthrough.
Request a walkthroughDutAIx provides assessment support, not legal advice or compliance certification. Results depend on configured coverage, project facts, supplied material and human review.