Illustrative walkthrough using seeded data. Product capabilities are marked Built or Planned.
NOTARY AI
Screen 04[BUILT]

Bereavement refund misstatement (NorthStar bot)

Customer Support · Consumer protection / BCCRT precedent (Moffatt v. Air Canada) — one entry in Company XYZ's versioned library of : preserved decision conditions paired with an Authorized Expected Behavior, reused on every future candidate version.
Company XYZ decision accountability · LoanCore Underwriting 3.2.0Customer Support · Case VR-NS-001Representative lending boundary case
  1. ACCOUNT13
  2. VERIFY47
  3. DEFEND89
  1. Connect
  2. Landscape
  3. Readiness
  4. 4Scenarios
  5. 5Authorize
  6. 6Verify
  7. 7Release
  8. 8Package
  9. 9Hand-off
VERIFYScreen 04
Question
Which decision conditions must future versions continue to handle correctly?
Answer
Company XYZ has preserved representative, boundary, disputed, and previously failed decisions as reusable Assurance Scenarios.
Output
A versioned library of decision conditions with authorized expected outcomes.
Fault attribution · Model hallucination

The LLM produced a policy statement with zero retrieved supporting documents.

Decision chain

[BUILT]captured evidence
INPUT
Customer message
'Bereavement fare — how do I get the refund?'
TOOL
Policy retrieval
0 documents matched (empty index)
MODEL
Failing or uncertain node
Support LLM v1.4
Generated answer without grounding
RULE
Grounding gate
MISSING — no citation-required check
DECISION
Reply sent
Message delivered to customer
Why this case is useful for release assurance
source_decision
Case VR-NS-001, bereavement fare
trigger
37 policy statements with no retrieval binding
failing_node
Support LLM v1.4
evidence_level
E3
replayability
Replay-ready from the sealed cassette
missing_evidence
Policy corpus was never ingested, so a contradicting source cannot be shown.
applicable_policy
Customer Communications Standard 2.0 (2026-03)
expected_behavior
Authorized by VP Customer Experience — Jordan Ochoa
suggested_preservation
Preserve decision-time policy version and human-review evidence on the next occurrence
suggested_scenario
Add to the Customer Support Release Scenario set as a customer challenge
Candidate provenance
evaluator
company-xyz-evaluator v0.6.2
frozen_input_set
customer-support-sweep-2026-07
evaluated_at
2026-07-22T04:15:00Z
source_evidence
sha256:d81a…4471
relationship_confidence
Confirmed — decision and adverse-action record share a source identifier
known_limitations
Detection limited to responses with structured retrieval logs.
Captured decision
Case VR-NS-001, bereavement fare
Outcome
TOLD CUSTOMER: 'apply within 90 days for refund'
reason: Response asserted policy; retrieval returned no matching document
Authorized Expected Behavior
Refuse to state a policy without a cited source document.
Evidence
E3sufficient for verification
cassette · sha256:d81a…4471
Next action

Advisory only. An must define or approve the expected behavior before a candidate version can be verified against it.

→ Authorize expected behavior
Screen anatomy

What this screen proves

For any single decision case, Notary AI can show which nodes ran, which node is failing or uncertain, what was captured, what evidence is missing, and what the record is at.

Why it matters

This is how a case earns a place in the release-assurance suite. A useful case has preserved evidence, a known applicable policy, and a clear expected behavior worth testing every future candidate version against.

Built or Planned

Planned capability for candidate generation; the decision-chain view and evidence grading are built. Candidates shown here are a seeded illustration.

Important boundary

The candidate is advisory. Notary AI does not determine what the acceptable outcome should be — an supplies the Authorized Expected Behavior on Screen 05, and the re-checks eligibility server-side.

Related requirements

Next

A scenario preserves the conditions, but it cannot decide what outcome is acceptable. An authorized Company XYZ reviewer must establish that.

Authorized Behavior