Platform | CTGT Policy Engine
Platform

From Probabilistic Guardrails to Deterministic Governance

CTGT's policy engine delivers what traditional guardrails cannot: real-time remediation, defensible audit trails, and consistent compliance enforcement across your entire AI deployment.

96.5%
Hallucination Prevention
3.3×
Accuracy Improvement
<10ms
Latency Per Token
100%
On-Prem Available
Core Capabilities

Built for Enterprise Scale

Four pillars that set CTGT apart from traditional AI guardrails and governance solutions.

01
End Model Micromanagement
Fine-tuning, RAG, and prompt engineering can consume 20-40% of total cost of ownership. CTGT's policy engine delivers consistent, compliant outputs without the constant iteration cycle that drains engineering resources.
02
Policy as Code
Teams spend countless hours painstakingly translating SOPs, policy manuals, and regulations into consistent model behavior. CTGT's Policy Engine ingests relevant business documents and intuitively understands your policy hierarchy, ensuring AI output is aligned at scale. Policy updates are no longer a nightmare with dynamic policy ingestion, integrated with your system of record.
03
Human in the Loop to Automated Remediation
Every org is different. That's why our platform is built to be modular from the ground up, so you can implement human in the loop review for every piece of flagged content, fully automated correction with state of the art remediation, or anything in between. You're in control.
04
Defensible Audit Trails
Companies in high-risk industries need deep insight into every part of their business, and GenAI shouldn't be an exception. Based on Stanford research, the Policy Engine evaluates adherence to your policies in a deterministic, transparent manner, ensuring that defensible audit trails pegged to your org's structure are always available for any generated content and remediation.
Head-to-Head Comparison
CTGT Advantage
Capability AWS / Azure Guardrails CTGT Policy Engine
Detection Method ●
Probabilistic classification; prone to false positives
 ✓
Deterministic graph-based reasoning with traceable logic
Real-Time Remediation ✗
Block or detect only with no content correction
 ✓
Automatically rewrites non-compliant output while preserving intent
Policy Ingestion ●
Manual rule configuration; limited preset categories
 ✓
Upload documents (SOPs, regulations); automatically translates into enforceable rules
Audit Trail ●
Basic logging; limited explainability
 ✓
Exam-ready trail linking each action to specific policy clause
Regulatory Compliance ✗
Generic categories; no industry-specific handling
 ✓
Built for SEC Reg BI, FINRA 2111, HIPAA, and custom regulations
Deployment Model ●
Vendor cloud only
 ✓
Full on-prem, VPC, or SaaS—data never leaves your environment
Enterprise Use Cases

Purpose-Built for Financial Services

From client communications to research summaries, CTGT ensures every AI output meets your compliance requirements without slowing down your teams.

Client Communications
Ensure all AI-generated emails, summaries, and correspondence comply with SEC Reg BI, avoiding forward-looking statements and unsubstantiated claims.
Research & Analyst Reports
Verify numerical accuracy against source documents, prevent quote exaggeration, and ensure proper attribution in AI-generated research.
Client-Facing Chatbots
Deploy AI assistants with confidence knowing they won't provide investment advice, speculation, or non-compliant responses to clients.
Internal Co-Pilots
Empower your teams with AI assistants that respect internal policies, brand guidelines, and confidentiality requirements across Outlook, Teams, and custom apps.
Performance

Benchmark Results

CTGT consistently improves model accuracy across hallucination detection and misconception resistance benchmarks.

HaluEval & TruthfulQA Performance
Verified Results
Model Base Accuracy With RAG Pipeline With CTGT Policy Engine
Claude 4.5 Sonnet 93.77% 84.88% 94.46%
Claude 4.5 Opus 95.08% 90.87% 95.30%
Gemini 2.5 Flash-Lite 91.96% 79.18% 93.77%
GPT-120B-OSS 21.30% 63.40% 70.62% (+49pts)

* HaluEval benchmark (hallucination detection accuracy) and TruthfulQA (misconception resistance). Full methodology available upon request.

Why Graph-Based Governance?

Deterministic Reasoning
Unlike probabilistic guardrails, our policy graph creates traceable decision paths, essential for regulatory audits and compliance reviews.
Semantic Understanding
The graph structure captures relationships between policies, enabling intelligent conflict resolution without blocking legitimate use cases.
Continuous Learning
Upload new policies as documents; the engine automatically translates rules and integrates them into the existing hierarchy. No engineering required.

Implementation Model

White-Glove Onboarding
Dedicated FTE from CTGT handles policy ingestion, integration, and testing. Typical deployment: weeks, not months.
Direct Technical Support
Work directly with our technical team via Slack. New features and changes deployed within weeks based on your feedback.
Proven Scale
Scoped for 10M+ daily messages for a systemically important financial institution. Enterprise-ready architecture.
Integration

Seamless Architecture

CTGT deploys as a governance layer between your LLM infrastructure and end users. No model changes required.

Your LLM
Azure / Bedrock / Any
CTGT Policy Engine
On-Prem Firewall
Governed Output
Remediated & Logged
End User
Internal / Client-Facing
"

It didn't just identify that there was a hallucination—it also showed that the hallucination stemmed from our own prompt. To me, that was a gamechanger.

Jonathan Sims — Head of Data & Analytics, Now Insurance (Inc. 5000 InsurTech)

Stanford Research
SOC-2 Compliant
On-Prem / VPC / SaaS
F500 Financial Clients
Backed by Google

Experience the next evolution of AI Governance

Our method represents a more advanced, programmatic approach to AI reliability that delivers accuracy beyond fine-tuning, RAG, and prompt engineering without the associated cost and complexity.

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