Seven-Point Record Defensibility Check
Work through one closed matter in your browser. Nothing is uploaded, and no sign-up is required.
Check a record →These tools help practitioners examine whether a consequential decision record preserves the basis, evidence, reasoning, and chronology needed for later independent review.
No purchase, account, or registration is required. Training is open without registration. Contact details are requested only if you choose to receive a named completion certificate and project updates with consent.
Public standard, controlled implementation. These practitioner materials explain and support use of the public JRS methodology. Review Engine source code, deployment architecture, and non-public evaluation infrastructure remain part of the controlled implementation.
Work through one closed matter in your browser. Nothing is uploaded, and no sign-up is required.
Check a record →Download the core review controls for use before a consequential record is finalized.
Download PDF ↓Keep the five review conditions and routing logic close at hand during a document review.
Download card ↓Apply JRS in employment and EEO, fair-housing, and international equality and human-rights investigation contexts.
Open the guides →Learn the method and apply the five conditions. All modules are open. Registration is optional and is used only for a named certificate and consented updates.
Begin training →Compare stronger and weaker records, identify reconstruction risks, and practice routing findings for human review.
Open simulations →Use concise references on chronology, context loss, escalation, reviewer boundaries, and other implementation concepts.
Browse the reference →Examine what has been tested, what the observed results establish, and what remains under validation.
Examine the evidence →Review the public schema, a constructed example, current-versus-target status, integrity controls, human-review requirement, and customer-controlled storage model.
Open the Manifest package →Hekim Colpan and Phillip Wikes examine how AI-assisted drafting can leave an employment record more polished than the evidence behind it, and describe a pre-finalization control for consequential records.
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