A Fortune 20 financial institution asked why every AI draft still needed two editors and a lawyer. Its LLM pipeline drifted from brand tone, missed required disclaimers, and introduced factual gaps. Compliance rejected 40% of first drafts.
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CTGT plugged into the same workflow and rebuilt control from the inside out.

The platform incorporates the firm’s brand guides, disclosure language, and relevant regulations into its feature set. Rather than a monolithic check, live data can be drawn in from the trading desk and other parts of the company to ensure triangulated, real-time compliance. Each requirement is linked to specific generation features, and every output includes a plain-language audit trail that shows how the model applied them. An intuitive networked graph displays hotspots of incompliant communication to gain insight on problem groups.
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Now their compliance team no longer has to hunt errors. It sets policy once and sees it enforced on every line.

A $13B fintech wanted to understand their customers on a deeper level with cohort analysis and segmentation powered by GenAI. However, much of their pre-existing workflows consisted of traditional ML workflows and large graphs with expensive updates.
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Rather than simply “one-shotting” an LLM at this data and losing nuance, leading to mediocre results, CTGT’s feature intervention technology directly links relevant features in traditional models to GenAI. This ensures that LLMs receive the information they need to do what they do best, like complex reasoning, while large quantitative analysis and other tasks are handled by existing performant methods. This is only possible because CTGT’s technology operates at the fundamental neural network level, as opposed to being beholden to a specific architecture.

Banks and wealth-management teams integrate CTGT through their existing model risk or content approval pipelines.
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The platform automatically ingests brand guides, regulation, and other relevant knowledge, and the newly robust outputs can be viewed under the supervision dashboards the compliance group already uses.
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Pilot outputs are reviewed against internal gold sets, and (because policy logic is encoded as features rather than fine-tuned weights) the model moves from pilot to full production well inside a quarterly audit window.
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Ongoing regulatory updates are handled by uploading a revised rule file, not by launching another training run, so CTGT stays aligned with every new bulletin without interrupting service or triggering a recertification cycle.