Policy as code
CTGT converts SOPs, regulations, and internal guidelines into machine-readable policy graphs that AI outputs are checked against automatically.
CTGT is an enterprise AI governance platform for regulated teams, with policy graphs, deterministic checks, audit trails, remediation, and model-agnostic control.
CTGT is an enterprise AI governance platform focused on accuracy, speed, and compliance in high-stakes environments. It presents itself as a deterministic layer for frontier intelligence, designed to control what AI systems do after they generate an output.
The product turns policies, SOPs, and regulations into machine-readable rules, then checks AI responses against those rules in real time. The result is a control layer with audit trails, policy enforcement, and remediation options for organizations that need governed AI rather than prompt-only guardrails.
CTGT says it is built for regulated and mission-critical workflows where teams want to deploy AI with more predictable behavior across changing business rules and policy requirements. The site also positions the platform as model agnostic, so governance can stay in place when underlying models change.
CTGT converts SOPs, regulations, and internal guidelines into machine-readable policy graphs that AI outputs are checked against automatically.
Every output is evaluated through deterministic logic, with traceable decision paths and audit trails that map to an organization’s structure.
The platform is described as model agnostic, so governance can persist across different model choices without rebuilding the control layer.
CTGT supports a range of remediation styles, from human review on flagged outputs to automated logic-level fixes before content is released.
The company says it can govern behavior without retraining, prompt hacks, or heavy fine-tuning, reducing the amount of model-specific tuning work required.
Financial institutions can apply policy graphs to customer communications, summaries, and assistant responses so outputs remain aligned with compliance rules and internal policies.
Teams replacing manual review with governed automation can use CTGT to flag or remediate outputs in real time instead of checking every response by hand.
Organizations that change models over time can keep a consistent governance layer in place while swapping underlying model providers or versions.
Teams that need auditable outputs can use CTGT to create traceable decision paths and logs for later review by compliance, legal, or operations stakeholders.
Enterprises that want policy-driven behavior control can encode business rules once and apply them across multiple workflows rather than managing separate prompt rules for each use case.
CTGT sits on top of an existing AI deployment and enforces policies at inference time. The source describes it as model agnostic and suitable for organizations that want governance without retraining or prompt-only controls.
The application form asks for a work email, organization, current model stack, governance objective, and technical context. That suggests the company is qualifying partnership requests and tailoring deployments to the customer’s environment.
The site positions CTGT for high-risk and regulated environments, including finance, insurance, media, and CPG. It emphasizes audit trails, policy enforcement, and deterministic remediation for outputs that need compliance review.
The site does not publish self-serve pricing. It references deployment with Fortune 500 partners and regulated institutions, which suggests a sales-led process rather than a public pricing page.