Product features
ConsentTrace turns evidence from external automation into validated, reviewable findings and region-relevant outputs—without becoming your testing framework.
Feature catalogue
Availability varies during the product build. Final scope is confirmed during a demo and commercial agreement.
Problem: Teams need to validate the workflow before API work is prioritised.
How it works: Upload evidence JSON through a controlled interface with the same validation contract used by integrations.
Outcome: Start evaluating evidence without waiting for a permanent pipeline.
Problem: Assurance needs to fit existing delivery pipelines.
How it works: Send versioned evidence payloads through a framework-independent REST API.
Outcome: Scale ingestion without replacing automation.
Problem: Incomplete or inconsistent evidence weakens downstream decisions.
How it works: Validate structure, required references and submission identity before evaluation.
Outcome: Know whether evidence is usable and why a payload was rejected.
Problem: Raw observations are difficult to govern over time.
How it works: Create structured findings linked to runs, regions, rules and evidence references.
Outcome: Give every issue a clear owner, state and history.
Problem: Declared inventories drift from observed runtime behaviour.
How it works: Import the customer inventory and compare it with cookies and technologies in submitted evidence.
Outcome: Surface unknown and unmatched technologies quickly.
Problem: A technology category may not match its observed behaviour.
How it works: Present the declared and suggested categories with confidence, reasons and evidence.
Outcome: Focus human review without presenting an automated legal conclusion.
Problem: Repeated known noise can overwhelm reviewers.
How it works: Mute a finding only within an explicit property, technology, rule or policy scope.
Outcome: Reduce noise while preserving traceability.
Problem: Classification changes require accountable decisions.
How it works: Record reviewer actions, evidence, reasons and accepted decisions.
Outcome: Create a defensible review history.
Problem: One global summary can hide regional context.
How it works: Generate reports using the relevant region profile and evaluation period.
Outcome: Provide carefully worded assurance outputs for governance.
Problem: Teams need findings in their own reporting systems.
How it works: Return result JSON, CSV findings and downloadable report files.
Outcome: Reuse outcomes without screen scraping.
Problem: QA teams need assurance results alongside broader quality signals.
How it works: Return structured results to HolisticQA as a result consumer.
Outcome: Keep the evidence producer and assurance outcome clearly separated.
Problem: A current status alone cannot explain how a decision was reached.
How it works: Link evidence, evaluation policy, finding changes and review actions.
Outcome: Reconstruct the assurance record over time.
Make evidence actionable
