The deterministic layer for frontier intelligence
Generative AI is probabilistic. Your business is not. We are the frontier lab opening the black box. CTGT replaces fragile guardrails with representation-level control that delivers the mathematical certainty and defensible audit trails required by the Fortune 500.
Mission
CTGT's technology is built upon a deeper understanding of how AI models internally represent and process information.
INDUSTRIES
Governance for mission critical applications
Total SEC, FINRA, and organization-wide compliance.
Instantly applied. No manual setup required.
Explore Insurance
30%
Boost in policy adherence
20-40%
Reduced total cost of ownership
97%
Policy updates in minutes, not months
Instantly adapt to a constantly changing policy environment.
Explore Insurance
68%
Improvement over CSP guardrails
$XX M
Saved for Inc. 5000 Insurtech
>20hrs
Saved from eliminated manual review
Ensure editorial tone is maintained in all generated content, at scale.
Explore Insurance
87%
Reduction in manual editorial review
100%
Ad & Legal disclosure adherence
One system for smarter workflows and on-brand social presence.
Explore Insurance
Engage with customers with on-brand responses, tuned to any platform
Simplify complex Excel-based workflows
Maintain brand consistency across sub-brands
The RAG failure in legal reasoning
Standard RAG pipelines broke the model’s legal reasoning capabilities, dropping accuracy to 39%. CTGT’s Policy Engine acted as a logic compiler, doubling performance to 78%.
Entity resolution
RAG introduces noise; CTGT adds signal. In identity resolution, RAG confused the model, causing a massive drop in accuracy. CTGT maintained 96% integrity.
Open source > Frontier models
Achieve up to 80% lower inference costs by pairing open-source models with CTGT’s Policy Engine. Governed OSS models deliver frontier-level reliability in policy-constrained workflows. 1
WHAT WE BUILT
How a Lloyd's-backed, Inc. 5000 InsurTech scaled AI powered underwriting with CTGT
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Deployment confidence
Enabled the safe transition
of LLM solutions from
internal use to high-stakes,
external production
environments.
Root-cause remediation
Shifted from basic
hallucination detection to
debugging the entire AI
stack, identifying critical
errors in prompt templates
and data pipelines.
Real-time governance
Implemented a centralised
policy engine ensuring AI
alignment and auditability
without sacrificing speed or
model flexibility.
Industry Perspectives
Validated by the Architects of Modern AI
From the creator of Keras to the leadership of the Fortune 500, the industry’s most demanding technical voices are aligning to CTGT's vision.
Zapier is the biggest automated AI platform in the world, and the #1 problem preventing businesses from adopting AI is low user trust. CTGT is developing a super novel approach that solves the unreliability and inherent limitations of modern AI to ensure that it's trustworthy for business needs.
I recently learnt about CTGT (YC F24)'s Policy layer that reduces hallucinations by ensuring necessary deterministic guardrails are setup to probabilistic agent outcomes specific to the industries that the Agentic systems have been setup for. Do check them out and let me know what you think
Mar 15, 2025
A feature-level approach to mitigating bias & censorship in deepseek-R1
Jun 28, 2025
Vibe coding lets novice software engineers generate code that looks usable without first mastering the fundamentals. But it often produces what... Cyril Gorlla, co-founder of enterprise AI company CTGT, calls “AI slop”: cheap, auto-generated, buggy code that demos well but collapses at scale.
Oct 08, 2025
Foundry announces the 2025 InfoWorld Technology of the Year Award finalists
Interesting technique for dynamically modulating censorship and bias in models.
I'm happy to see [CTGT’s approach to AI] off the beaten path - our field needs more research diversity. In particular we need more approaches focused on compute efficiency & data efficiency.
I recently learnt about CTGT (YC F24)'s Policy layer that reduces hallucinations by ensuring necessary deterministic guardrails are setup to probabilistic agent outcomes specific to the industries that the Agentic systems have been setup for. Do check them out and let me know what you think
I recently learnt about CTGT (YC F24)'s Policy layer that reduces hallucinations by ensuring necessary deterministic guardrails are setup to probabilistic agent outcomes specific to the industries that the Agentic systems have been setup for. Do check them out and let me know what you think
I recently learnt about CTGT (YC F24)'s Policy layer that reduces hallucinations by ensuring necessary deterministic guardrails are setup to probabilistic agent outcomes specific to the industries that the Agentic systems have been setup for. Do check them out and let me know what you think
I'm happy to see [CTGT’s approach to AI] off the beaten path - our field needs more research diversity. In particular we need more approaches focused on compute efficiency & data efficiency.