Oracle RAI Partnership
Deterministic AI Governance
at Enterprise Scale
CTGT's policy graph delivers what guardrails cannot: active remediation,
collision resolution, and audit-grade compliance for Oracle's AI portfolio.
89%
Auto-Remediation
Accuracy
45K+
Policies with
Collision Handling
The Guardrail Gap
Current State Challenges
- Binary guardrails fail on nested, contradictory policies
- No remediation capability, only blocking
- Models easily tricked by adversarial inputs
- No defensible audit trail for regulators
- Fine-tuning is expensive and doesn't scale
CTGT Resolution
Production-Ready Today
- Neo4j policy graph with collision resolution
- Active remediation preserves user intent
- Feature-level intervention for open-weight models
- Complete audit trail for every decision
- On-prem deployment, SOC-2 certified
Technical Alignment with Oracle RAI Vision
Knowledge graph for policy selection (in production)
Nested policy handling with deterministic resolution
Hybrid ML + LLM approach (graph verification)
Full on-premise deployment available
"It didn't just identify the hallucination, it traced it back to our prompt template.
That's what changed everything for us."
Jonathan Sims, Head of Data & Analytics, Now Insurance (Inc. 5000 #9)
Engagement Timeline
1
Technical Deep-Dive
Week 1-2
Architecture review with Oracle RAI engineering team
2
Proof of Concept
Week 3-6
Single use case deployment: HCM agents or hiring
3
Production Pilot
Week 7-12
Scale to production with Oracle policy sets
4
Integration
Ongoing
Embed as Oracle's AI governance layer
Schedule Technical Deep-Dive
Working demo in your environment within days