CTGT provides a deterministic governance layer for enterprise generative AI that converts SOPs and regulatory texts into executable policy code, automatically validating every model output against these rules. The platform delivers audit‑ready decision logs, configurable human‑in‑the‑loop workflows, and out‑of‑the‑box model control, reducing engineering overhead while ensuring compliance and brand consistency for high‑risk sectors.
Funding
$7.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
1OFounders
Product
Problem
Enterprises using generative AI face unpredictable outputs that can violate internal policies, regulatory requirements, and brand standards, leading to compliance risk and costly manual remediation. Existing guardrails are often probabilistic and lack transparent auditability, making it difficult to guarantee deterministic behavior for mission‑critical applications.
Solution
CTGT delivers a deterministic governance layer that translates an organization’s standard operating procedures and regulations into machine‑readable policy code. The platform validates every AI‑generated output against these rules, providing a mathematically certain, audit‑ready decision log mapped to the company’s structure. Users can configure the level of human oversight, from full manual review of flagged results to fully automated logic‑level remediation. By embedding policy enforcement directly into the model’s execution, CTGT eliminates the need for extensive fine‑tuning, retrieval‑augmented generation (RAG) hacks, and prompt engineering, reducing engineering overhead while improving policy adherence and compliance.
Target Audience
Primary customers are large enterprises in high‑risk sectors—such as finance, insurance, media, and consumer packaged goods—that require strict regulatory compliance and brand‑consistent AI outputs.
Features
- Policy‑as‑code engine that converts SOPs and regulatory texts into live, executable rules governing AI behavior
- Deterministic validation of each model output with transparent, structured audit trails linked to organizational hierarchy
- Configurable human‑in‑the‑loop workflow for flagged outputs, supporting both manual review and automated remediation
- Out‑of‑the‑box model governance that removes reliance on fine‑tuning, RAG pipelines, and prompt hacks
- Performance boosts demonstrated in legal reasoning (accuracy from 39% to 78%) and entity resolution (maintaining 96% integrity)
- Integration hooks for enterprise systems to enforce compliance with SEC, FINRA, and other industry standards