AI Decision Assurance with Scenario Intelligence

Stop repeating AI failures.

Notary captures real AI decisions as sealed evidence, replays failures, verifies fixes against the same recorded conditions, and turns overrides into regression tests for future releases.

View interactive demo Install the SDK

The clock is regulatory, not just competitive.

Regulatory pressure is moving from policy to examination. NAIC AI governance expectations are being operationalized through AI evaluation toolling in 2026. The EU AI Act's high-risk obligations apply from December 2027. Insurers, lenders, and health plans need evidence of remediation and release controls before examiners ask.

Observability shows what happened. It can't prove why.

When an autonomous AI agent fails in production, your logs show the error — but not the cause, and not that your fix actually works. Regulators require more. The EU AI Act, NIST AI RMF, SEC disclosure rules, and OCC guidance all demand forensic proof: what went wrong, why, and evidence the fix prevents recurrence.

$5M–$500M
Potential fines
8–12 weeks
Typical investigation
Most tools
Stop at what happened
Notary is the execution runtime that makes an agent run reproducible and its remediation provable.

Git for AI agent execution.

Capture → commit
Every prompt, tool call, and decision recorded as a node in a sealed execution graph.
Replay → checkout
Deterministically re-run the exact incident from the sealed cassette. No production system called.
Branch → experiment
Fork the run and try a fix without touching the original.
Diff → compare
See exactly where and how the fixed run diverges.
Verify → certify
Prove the fix resolves the incident. Issue a signed certificate.

Tamper-evident capture

HMAC-SHA256 sealing with a Merkle chain. Alter one byte and the proof breaks.

Deterministic replay

Replay runs from sealed cassette by default. Sandbox is an escalation path where configured. Production is capture-only.

Proof of Mitigation

A cryptographically signed certificate regulators and courts can verify independently.

Beyond one failure at a time

Your decision history is a scenario mine, not a log.

Every escalation, override, denial, and complaint your AI agents have produced is a candidate scenario. Notary clusters historical decisions by intent, outcome, policy, and override pattern to surface failure modes your team may not have reviewed yet. Each candidate is checked for replayability and labeled with the customer-approved expected outcome before it enters your release gate.

In a mid-size contact center, this can mean hundreds of candidate scenarios a month — failed handoffs, human overrides, complaints, and policy breaches that usually disappear into transcripts.

Novel Scenario Discovery

Cluster overrides, escalations, denials, and complaints to surface recurring failure patterns your team may not have reviewed.

Policy Gap Analysis

Compare stated policy against actual AI outcomes and human overrides to find where your agent drifts from intent.

Regulatory Scenario Mapping

Map candidate scenarios to HIPAA, FCRA, GLBA, NAIC, ADA, and EU AI Act obligations where applicable.

Managed Library Expansion

Notary surfaces candidates monthly. Your team labels expected behavior. The scenario library compounds over time.

How records enter Notary

Automatic capture

SDK captures agent decisions in production. Every prompt, tool call, and output is sealed as it happens.

📤

Send to Notary

Reviewers send tickets, claims, escalations, or complaints from source systems directly into Notary for analysis.

🔍

Scenario Intelligence

Historical records are clustered into candidate scenarios, checked for replayability, and labeled with expected outcomes.

Four failure patterns Notary turns into proof

Each scenario is a real decision captured, replayed, fixed, verified, and added to your release gate.

Lead Scenario

Customer-service failed handoff

Original failure:Customer asks for a human three times. Bot keeps answering with FAQ. Human overrides and escalates.
Recorded conditions:Three "speak to agent" intents, bot confidence scores, FAQ responses, final override timestamp.
Expected behavior:Escalate to human after second "speak to agent" request.
Fix:Customer developer updates escalation policy: escalate after 2nd human request.
Replay proves:Fixed agent outputs ESCALATE_TO_HUMAN under the same recorded conditions. Cassette replay — no production call, no sandbox required.
Release gate check:Future AI support-agent releases must pass: failed_handoff → ESCALATE_TO_HUMAN
Lending

Qualified borrower denied

Original failure:Lending agent denies applicant: credit score 650, threshold 700.
Recorded conditions:Credit score, threshold policy, application data, decision timestamp.
Expected behavior:Approve applicant with score ≥ 620 under updated policy.
Fix:Customer developer lowers internal threshold to 620.
Replay proves:Notary replays the captured decision from the sealed cassette — the exact recorded score and policy context. No production system called. Because the fix changes only internal threshold logic, cassette replay is enough to verify.
Release gate check:Future lending releases must pass: score_650_threshold_620 → APPROVE
Healthcare

Necessary care auto-denied

Original failure:Prior-authorization agent denies a medically necessary procedure. Clinician overrides.
Recorded conditions:Procedure code, clinical criteria, agent rationale, override reason, clinician notes.
Expected behavior:Approve procedure when clinical criteria are met per updated policy.
Fix:Customer developer updates clinical criteria matching logic.
Replay proves:Fixed agent approves under the same recorded clinical conditions. Sealed cassette replay; sandbox not required for this fix.
Release gate check:Future prior-auth releases must pass: necessary_care_criteria_met → APPROVE
Hiring

Qualified candidate rejected

Original failure:Screening agent rejects qualified candidate due to biased keyword filter. Recruiter overrides.
Recorded conditions:Resume text, filter keywords, match scores, rejection reason, override note.
Expected behavior:Advance candidate when qualifications match role requirements.
Fix:Customer developer removes biased keyword filter from screening logic.
Replay proves:Fixed agent advances the candidate under the same recorded resume and role data. Sealed cassette replay.
Release gate check:Future screening releases must pass: qualified_candidate → ADVANCE

From AI failure to release gate

Instrument the agent. Replay the failure. Verify the fix. Add the scenario to the next release gate.

1

Capture the decision

from notary import instrument @instrument(secret_key=NOTARY_KEY) def run_agent(request): return agent.decide(request)

~5 lines. Every run sealed as it happens.

2

Replay from sealed cassette

▶ Replay incident from sealed cassette

No production call. No sandbox required unless the fix introduces new external behavior.

3

Verify the fix

✓ Verify scenario
Expected: ESCALATE_TO_HUMAN
Fixed output: ESCALATE_TO_HUMAN
Result: verified for this scenario
4

Add to release gate

⊕ Add scenario to release gate

Scenario saved: failed_handoff → ESCALATE_TO_HUMAN

Future releases must pass this scenario.

Notary verifies that the fixed agent produced the customer-approved expected outcome under the recorded scenario conditions. It does not certify general AI safety.

Not observability. Not QA analytics. Decision assurance.

Observability sees failures. Analytics measures them. Governance tools document policies. Notary replays real failures, verifies fixes, saves scenarios, and gates future releases.

Most tools tell you an eval score changed. Notary proves the exact recorded failure no longer reproduces under the same conditions that caused it the first time. That's the difference between probably better and verified fixed.

CategoryWhat it does
ObservabilityTraces, logs, latency, errors
Contact-center analyticsHandoff rate, CSAT, QA scores
GovernancePolicy approvals, inventories, risk registers
NotarySealed replay, fix verification, scenario library, release gate, proof

One proof layer. Every accountable team.

Operations, compliance, legal, and AI teams get the same answer: what failed, what fixed it, and whether the next release will repeat it.

Operations / CX

Stop repeat AI failures.

A mid-size contact center escalates thousands of AI conversations a month. Most overrides disappear into QA notes and transcripts. Notary converts them into a compounding replay suite so the failure your agents corrected last week cannot ship again next quarter.

Recurring usage, not a one-time audit.

Compliance / Legal / Risk

Prove remediation.

Show what happened, why it happened, how it was fixed, and that the proof was not altered.

Chain of custodyFix proofAudit readinessRegulator evidence

AI Platform / Engineering

Test against real failures.

Replay production failures before every prompt, model, policy, or code release.

Regression suiteRelease gateReal scenariosNo synthetic-only evals

Executives / AI Transformation

Scale AI without repeating failures.

Keep automation gains while controlling risk, support quality, and release confidence.

AI qualityRisk reductionBusiness continuityTrust at scale

Start with core replay and fix verification. Add Scenario Intelligence, regulatory packs, and managed library expansion as your AI footprint grows.

Four proofs, one sealed record.

Causation

What decision was made, and why.

Remediation

The fix produced the customer-approved expected outcome under the same recorded conditions.

Integrity

The evidence has not been altered.

Durability

The proof remains verifiable from sealed evidence years later.

Notary verifies that the fixed agent produced the customer-approved expected outcome under the recorded scenario conditions. It does not certify general AI safety.

Release gate maturity

Today, Notary flags scenario failures for manual release review. Automated CI/CD gating is the next step.

Notary verifies that the fixed agent produced the customer-approved expected outcome under the recorded scenario conditions. It does not certify general AI safety.

Evidence you don't have to take on faith.

Bring your own key

Seal runs with your own key; Notary never has to hold it.

Publicly verifiable signatures

Certificates signed with asymmetric keys (ECDSA/RSA) — verify with a public key, no secret required.

Immutable audit trail

Append-only, write-once evidence log. Nothing can be silently altered.

GRC-native

Evidence flows into ServiceNow, OneTrust, and AuditBoard, mapped to the right controls.

Built for the frameworks that matter.

EU AI Act (Article 10) NIST AI RMF SEC AI Disclosure OCC Model Risk HIPAA FCRA GLBA NAIC ADA

Pricing

Three tiers. Start free. Scale as your AI footprint grows.

Free RECOMMENDED
Professional
Enterprise
PriceFree foreverContact usCustom
ForDevelopersCompliance + legalLarge orgs, critical infra
SDK: capture + HMAC sealing + local verify
Framework supportRaw / basicAll frameworksAll + custom
Deterministic replayLimited (free quota)UnlimitedUnlimited
Live sandbox validation (escalation)Select providers where configuredCustom sandbox providers
Branching & experiments1 branch / incidentUnlimitedUnlimited
Scenario Intelligence / Managed LibraryIncluded / limitedCustom / managed
Mutation testingManualAutomatedAutomated
Proof of Mitigation certificates
Certificate signatureECDSAECDSA + RSACustom
Compliance reportsAll frameworksCustom
GRC connections5Unlimited
Audit logging / RBAC
SSO
SLA99.5%99.9%
SupportCommunityPriorityDedicated
Data retention30 days1 yearCustom
Install the SDKContact usTalk to sales

Usage limits and pricing shown are indicative and subject to change.