Deterministic AI Governance Runtime

Deterministic Governance
for AI Systems

Control when inference happens.

Verify every critical claim.

Replay every decision.

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Decision Control
When inference happens
Claim Integrity
What leaves the system
Audit-Ready
Replayable decisions
Vendor-Agnostic
Works across providers

The Problem

AI systems in enterprise environments face fundamental governance challenges.

LLMs generate probabilistic outputs.

Enterprise systems require reproducibility and accountability.

Unverified claims introduce operational and regulatory risk.

AI decisions are difficult to explain post-factum.

Three Governance Pillars

SSAP provides a complete governance framework for AI systems.

Decision Control

SSAP Core

  • Formal execution graph (PROBE → FULL → BLOCK)
  • Bounded escalation (max 1 retry)
  • Policy-versioned decision paths
  • Vendor-agnostic model routing

Claim-Level Integrity

Enforcement

  • No unverified claims in Required mode
  • Evidence-bound output structure
  • Claim-by-claim verification status
  • Hard blocking on FAIL

Deterministic Audit

Replay

  • Decision path logging
  • Policy snapshotting
  • Evidence snapshot references
  • Replayable execution traces

Execution Graph

Bounded, deterministic control over every AI decision.

PROBE
LLM_PROBE
INTEGRITY
PASS
RETURN

Verified response delivered

FAIL
ESCALATE

Bounded retry initiated

Escalation Path (max 1 retry)

FULL
INTEGRITY
PASS → RETURN
FAIL → BLOCK

Claim-Level Verification

Every claim is verified against evidence before leaving the system.

Evidence-Bound Output

Each claim is linked to a specific evidence reference with document ID and section.

Verification Status

Claim-by-claim verification with PASS/FAIL status. Hard blocking on unverified claims.

Decision Path Tracing

Full audit trail with policy version, integrity mode, and execution path.

Structured Output Example
{
  "decision_path": "PROBE_ESCALATED_FULL",
  "claims": [
    {
      "claim_id": "c1",
      "text": "Interest rate is 3.25%",
      "evidence_ref": "DOC_2026_TARIFF_V3#section4",
      "verification_status": "PASS"
    }
  ],
  "policy_version": "FIN_PACK_v1.2",
  "integrity_mode": "REQUIRED"
}

Enterprise-Grade Governance

Defensible claims backed by deterministic execution.

Deterministic execution layer over LLM systems
No unverified claims in Required mode
Replayable and audit-ready AI decisions
Vendor-agnostic AI governance
Bounded adaptive risk control

Secondary Benefits

Additional advantages from structured inference control.

Cost Optimization

Side-effect of structured inference control

Latency Control

Bounded escalation paths

Risk Adaptation

Thresholding based on domain signals

Model Portability

Cross-model without governance redesign

Request Governance Brief

Tell us about your AI governance requirements. We'll send you a tailored brief within 24 hours.

Enterprise Inquiry

Direct Contact

Prefer email? Reach us at marko@ssap.io

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Access real-time metrics, decision logs, and governance reports.

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