Illustrative walkthrough using seeded data. Product capabilities are marked Built or Planned.
NOTARY AI
Screen 06[BUILT]

Candidate Verification

Three frozen inputs — preserved decision evidence, the immutable candidate artifact, and Authorized Expected Behavior. Result states: Verified, Failed, Inconclusive, System error, Not run. Inconclusive never passes. Method: .
Company XYZ decision accountability · LoanCore Underwriting 3.2.0Customer Support · Case VR-NS-001Policy statement produced with no retrievable source document
  1. ACCOUNT13
  2. VERIFY47
  3. DEFEND89
  1. Connect
  2. Landscape
  3. Readiness
  4. Scenarios
  5. Authorize
  6. 6Verify
  7. 7Release
  8. 8Package
  9. 9Hand-off
VERIFYScreen 06
Question
Does LoanCore 3.2.0 produce Company XYZ's authorized outcome under the preserved conditions?
Answer
Under the scoped A-1027 conditions, the candidate routes the applicant to compensating-factor review as authorized.
Output
A reproducible comparison between approved version 3.1.4, candidate version 3.2.0, and Authorized Expected Behavior.
Comparison result
Not run
Approved northstar-support-1.4.0
TOLD CUSTOMER: 'apply within 90 days for refund'
Candidate northstar-support-1.5.0
Pending run
Authorized Expected Behavior
REFUSE_AND_HANDOFF

Scoped to the preserved Applicant A-1027 conditions and this scenario's bindings. This does not claim candidate northstar-support-1.5.0 is correct, safe, or compliant in general — only that it matches Authorized Expected Behavior under these recorded conditions. Result states: Verified, Failed, Inconclusive, System error, Not run. Inconclusive never passes.

Boundary

Notary AI does not modify production and does not author fixes. Engineering supplies an immutable candidate artifact; Notary AI replays preserved decision scenarios against it in a controlled environment and reports whether the candidate matches the authorized expected behavior.

Candidate artifact

[BUILT]verification run
baseline_version
northstar-support-1.4.0
candidate_version
northstar-support-1.5.0
artifact_digest
sha256:71bd…33ce
source_commit
c02ea91
change_type
configuration + prompt
submitted_by
NorthStar Conversational AI
change_summary
Require a cited source document before any policy statement; otherwise hand off
Declared behavior changes
  • require_citation
    falsetrue
    Refuse if retrieval returns 0 docs
  • fallback_response
    generativehandoff_to_human
    Uncited policy questions escalate
Evidence sufficiency
E3N=20 sampled, ≥95% agreement

Verification run log

N=20 sampled, ≥95% agreement
Waiting for replay…
Screen anatomy

What this screen proves

Given a preserved decision scenario and the customer's , Notary AI can reproduce what the baseline version decided and then show what the candidate version decides — under decision-time context bindings, not current settings.

Why it matters

This runs on every candidate release, not only after an incident. It is how a vendor answers "does this version still behave the way we authorized?" before deployment rather than after a complaint.

Replay method: exact or sampled

N=20 sampled, ≥95% agreement. Language-model decision — non-deterministic. Confidence disclosed on the certificate.

Exact replay works when the decision is fully rule- or feature-driven. Language-model decisions use N-sample verification with a disclosed confidence threshold; the certificate states which was used.

Decision-time context bindings

A pins the policy version and configuration in effect when the original decision was made. Verification runs against those bindings, so a passing result describes behavior under real recorded conditions.

Built or Planned

Built capability. Deterministic replay and candidate verification against authorized expected behavior exist today. Independent third-party verification packages are planned.

Related requirements

Next

Verification produces evidence, not authority. Company XYZ's accountable owner must make the release decision.

Release Decision