A hold state prevents an AI-generated internal deliverable from progressing when required evidence, review authority, or accepted assertions are missing.
Name every reason the workflow must stop
List unsupported claims, failed deterministic checks, inaccessible evidence, stale sources, reviewer absence, disputed classification, prohibited use, unresolved escalation, and expired approval as explicit states. Define the unit of work, the people and systems involved, the evidence already available, and the exact decision this record must support. A narrow boundary keeps the analysis tied to an observable process instead of turning it into an open-ended inventory.
NIST's governance and management functions require assigned responsibility and treatment of identified AI risks, which supports explicit ownership and disposition records. Preserve the source URL, version, retrieval date, and relevant rule beside the local implementation decision. If the source does not address the buyer's environment directly, label the local conclusion as an adaptation and retain the assumption that connects them.
Route holds to accountable owners
A hold record should name the output, risk tier, failed assertion, evidence, owner, entered time, required correction, escalation deadline, reviewer decision, and released revision. Each record needs a stable identifier, owner, current state, source reference, last verified time, exception path, and next permitted action. Conflicting or missing evidence remains visible so a later reviewer can distinguish a confirmed result from inference, recollection, or an unavailable signal.
Only the named buyer reviewer may release a hold after the required evidence or correction appears, while prohibited decision classes remain outside the workflow. Write the decision rule before automating it, including who may approve, what evidence is required, which condition causes a hold, and how an exception expires. This makes the control testable and prevents a tool from quietly expanding its own authority.
Verify release cannot bypass the gate
Attempt direct publish, stale approval reuse, reviewer substitution, changed output after approval, unresolved escalation, missing evidence, and release from the wrong risk tier. Record the fixture, versions, environment, expected result, actual result, reviewer, and corrective action for every failed case. Rerun the accepted cases after a source, permission, workflow, or dependency changes so an old passing result is not presented as current evidence.
Human Review and Acceptance Control System is operated by Reality Contact, LLC. The buyer excludes consequential decisions and retains every final judgment; Reality Contact, LLC implements only the accepted internal review and evidence workflow. The resulting guide and implementation evidence cover only the named sources, workflow, versions, and acceptance cases, so the buyer retains authority over policy, credentials, production use, and later changes.
Where the service stops
Reality Contact, LLC implements bounded review controls but does not make regulated or high-impact decisions, replace accountable reviewers, verify every source, provide legal advice, approve production, or operate review indefinitely. The buyer excludes prohibited decisions, appoints accountable reviewers, confirms evidence and risk tiers, retains every final decision, and approves which internal deliverables may enter production. This is technical workflow implementation and document preparation; it does not replace professional legal, compliance, privacy, security, editorial, or domain review. The system does not promise factual correctness, unbiased judgment, complete source coverage, or safe use outside the accepted internal deliverables and calibration cases.
Sources: NIST AI Risk Management Framework; LangSmith evaluation documentation.