CTGT
Interpretability lab constraining AI models to organizational policy at output
CTGT is an applied interpretability lab that studies how frontier models behave in mission-critical settings and provides a policy engine that constrains any model to complex organizational policy at the moment of output. Its research isolates and modifies specific features inside neural networks that govern behavior through direct intervention at the representation level, rather than through retraining or prompting. The approach is intended for organizations that need AI to operate reliably within real-world constraints, including regulatory requirements and evolving business rules.
The Policy Engine applies deterministic policy graphs governing agent outputs at inference time, with cryptographically attestable audit trails. CTGT's work spans mechanistic interpretability, feature-level bias and censorship mitigation, entity resolution, and retrieval-augmented generation workflows. The company describes finance and insurance as target industries, with applications covering SEC, FINRA, and organization-wide compliance. Access is available through a request-based process; the pages do not specify a free plan, trial, or pricing model.
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