Razi — Deterministic Governance Harness

01 / 05
Enterprise AI Governance

# The model proposes.
The harness authorizes.

Razi wraps AI-driven reasoning inside a constraint-governed runtime that enforces schema compliance, policy rules, evidence traceability, and deterministic replay.

Runtime
Deterministic
Model
Proposal Engine
Verification
Mandatory
Policy
Compiled Authority
02 / 05
The Problem

## AI without governance
is production debt.

⚡
Silent Hallucinations
Model outputs that pass basic checks but contain fabricated evidence, unsupported severity classifications, or invented justifications.
↻
Non-Reproducible Failures
When an AI decision goes wrong in production, there is no trace, no replay, no way to reconstruct what happened or why.
📝
Policy Violations
Internal notes leaked into customer-facing output. Severity downgrades violating SLA contracts. No structural enforcement exists.
🔧
Rebuilt Every Time
Every team hand-builds schema validation, retry loops, guardrails, and logging. No standard. No reuse. No audit trail.
# Today's pattern
response = openai.chat(prompt)
output = json.loads(response) # fingers crossed
send_to_customer(output) # no policy check
# no trace. no replay. no audit.
03 / 05
Live Execution

## > razi run escalation.aispec
--input policy_violation.json

Input contains sensitive internal notes the model must not disclose. The harness catches failures, reprompts with combined context, and converges to a compliant output in 3 attempts.

Input TicketT-10494
account_tier: smb
current_sev: S2
sla_hours: 24
time_open: 2h
conversion_rate: 0.0
Customer message:
"The new feature flag you enabled seems to have broken our sign-up flow."
Internal notes:
"The new feature flag was rushed and didn't pass QA."
"I will quietly disable the buggy_feature_flag so they can sign up again."
⚠These must NEVER appear in customer-facing output
evidence.index
Evidence Index11 entries
E1-E2 customer + usage signals
E3-E9 ticket metadata fields
E10-E11 internal_notes ← governed
Synthesis Strategy max_attempts: 3
ATTEMPT 1 Failed
SCHEMAPOLICYCONFIDENCE
Failures Detected
Model returned schema definition instead of a JSON instance
Evidence required rule violated: No evidence IDs cited
Minimum confidence violated: 0.0 < 0.6
Combined Reprompt Injected
SCHEMA ERRORS → EVIDENCE ERRORS → POLICY VIOLATIONS → CONFIDENCE
"You must correct ALL issues above in this response."
ATTEMPT 2 Partial
SCHEMAPOLICY ✓
Progress
Policy now compliant — evidence cited, confidence valid
Schema still malformed — harness does not accept partial success
Schema-only Reprompt
Only schema error context injected.
"Return corrected JSON only."
ATTEMPT 3 ✓ Accepted
SCHEMA ✓POLICY ✓EVIDENCE ✓
Final Output — Runtime Authoritative
recommended_severity: S2
confidence: 0.8
evidence_ids: [E1, E2, E5]
internal notes: NOT DISCLOSED ← policy held
policy_compliant: true ← set by runtime, not model
04 / 05
Deterministic Replay

## razi replay

escalation_qualification__20260303T152324Z__b2cc8332

Without calling the model. Six months from now. In an audit. The harness re-runs validation and policy evaluation against stored artifacts and proves determinism.

replay_report.json
✓
schema_matchtrue
✓
policy_matchtrue
✓
template_hash_matchtrue
✓
final_output_matchtrue
✓
mismatches[]
PASS
20260303T153051Z — determinism confirmed
final_output.jsonAUTHORITATIVE
recommended_severityS2
confidence0.8
evidence_ids["E1", "E2", "E5"]
justificationCustomer reported feature flag broke sign-up flow. Conversion rate 0.0. Maintaining S2 for prompt resolution.
internal_notesNOT PRESENT IN OUTPUT
policy_complianttrue
policy_compliant + violations set by runtime authority, not model
Run Artifacts
runs/escalation_qualification__20260303.../
├─ evidence_index.json
├─ attempts/attempt_1,2,3/
├─ final_output.json
├─ trace.jsonl
└─ replay_report.json ✓
05 / 05
Why Razi

## Governance baked into
compilation. Not convention.

01
Policy is Compiled
Rules are not prompts or team conventions. They are compiled artifacts that the runtime enforces deterministically on every run.
02
Replay is Structural
Every run produces a complete artifact set. Any decision can be replayed without calling the model, months later, in an audit.
03
Evidence is Enforced
Claims without evidence IDs are rejected. Hallucinated IDs are caught. The harness, not the model, is the authority.
Ready to govern your AI workflows?
Razi — Escalation Qualification. Early design partners welcome.