CTGT

Appreciate the conversation on accountable AI with @DataInnovation . At @CTGTInc, we’re focused on helping teams detect, correct, and document unreliable or biased AI outputs in real time, so AI systems can be trusted in production, not just in theory. Thanks for featuring our work.

🔗 forbes.com/sites/digital-…

🚀 Thrilled to share CTGT was named one of Forbes’ Top 12 Companies Redefining Personalization With Web3, AI, Robots at #CES2026! Huge thanks to Forbes, our team, partners & clients 🙌 Together, we’re redefining AI governance, making intelligent systems trustworthy & accountable.

2025 wrapped: It was a tough year being steeped in the "trough of disillusionment" with GenAI. Enterprises exhibited lower confidence than ever that AI could actually be a force multiplier for their orgs. But what I'm most proud of isn't what's in this picture. Of course, a rapid growth in our F500 deployments and our public launch getting to the front page of HN, is great, but what I find truly exceptional is the team we've built. We brought on star operational and engineering team members that allowed us to handle complex application environments and bureaucratic internal processes that would've typically taken a team 5-10x our size. Our most notable accomplishment this year is breaking through the noise in what I glibly characterize as a sea of slop - amongst countless evals, observability tools, fine-tuning platforms etc. our message of removing the friction between regulated industries and non-deterministic AI resonated at the highest levels.

🚨 Why this matters for enterprises CTGT lets teams: - Elevate cheaper OSS models to frontier reliability - Reduce compute costs - Deploy AI safely in finance, law, and customer service 📊 Full benchmarks: ctgt.ai/benchmarks 🧪 Playground (free, no signup): playground.ctgt.ai 📩 Want to optimize internal models or workflows? ctgt.ai/contact-us AI reliability needs governance, not just bigger models.

🧪 What we benchmarked against We compared CTGT to strong, common baselines: - Standard prompting - Enterprise RAG pipelines - Constitutional / system-prompt approaches Our major findings: - RAG often degrades reasoning (adds noise, not logic) - Prompts fight pre-training priors - Constitutional prompts increase refusals, not correctness The team at CTGT has built a model that outperforms all three across every competitor model tested.

🚨 New Benchmarks: 3.3× accuracy. +49 truthfulness points. 96.5% hallucinations blocked. Improvements across all frontier model families (OpenAI, Gemini, Claude). We’re CTGT, a product-focused mechanistic interpretability lab building activation-level control for LLMs. Our policy engine dramatically improves accuracy and eliminates hallucinations, delivering 3.3× accuracy gains on TruthfulQA +49 pts truthfulness 96.5% hallucination prevention on HaluEval Results span across open-source + frontier models on real enterprise benchmarks. Thread 👇

Over the last 3 weeks, the team @ctgtinc has been pulling late nights + long weekends. We are not a billion dollar AI company, we are a small team <15 with huge conviction that there’s a need to deploy AI safely in domains like finance, law, and support.

Read more about it here: ctgt.ai/blogs/introduc…

Today we launched Mentat, an OpenAI-compatible API that gives builders deterministic control over LLM behavior. CTGT-governed models now deliver frontier-level reliability. In our evaluations, GPT-120B-OSS reached 96.5% hallucination reduction on HaluEval, surpassing frontier models like Gemini 3 and Claude 4.5 Opus. All of this is powered by CTGT’s Policy Engine, which evaluates content in real time against an organization’s rules and trusted information. We are building the infrastructure that lets companies move from “AI that usually works” to AI they can trust every time.

CTGT was recognized in the governance category of the 2025 @InfoWorld Technology of the Year finalists by @FoundryCo_Inc. This is a meaningful milestone and reflects the trust our customers place in our approach to AI governance. Reliability and control now determine whether a system can operate at enterprise scale. All finalists here: bit.ly/48FhR7B

Not every day you see this guy on your AI governance platform. The "we build it all in-house" meeting must have gone poorly.

Both @octolane and @CTGTInc included in this piece in the @sfstandard on time management for tech startup founders: sfstandard.com/2025/10/01/hac…

@CyrilGorlla Full @sfstandard article by @reeyopeeyo here: sfstandard.com/2025/09/16/san…

If you're not doing at least 996, you're not serious about building. The Manhattan Project did not run on balanced schedules. Apollo was not built on summer Fridays. People talk about 996 like it's a meme, but some problems dictate the hours. Building AI that can withstand compute limits, scaling law failures, and collapse under real-world pressure does not happen within a nine-to-five schedule. I tell my team this is temporary. It is the beginning of an exponential curve. We work 70+ hours a week at @CTGTInc because that is what the work requires. What comes next compounds tenfold, fiftyfold, a hundredfold, and the people who put in the work now will be the ones shaping it.

How San Francisco became the ultimate ‘996 City’ sfstandard.com/2025/09/16/san… via @sfstandard (features @CTGTInc)

It’s a tough time to be a young person looking for a job, unless you’re in AI. Companies are snapping up “AI native” talent straight out of school—no work experience required. wsj.com/tech/ai/ai-job… via @WSJ (features @CyrilGorlla and @CTGTInc)

The quality and density of talent in the age of AI is unprecedented. There's a lot more slop, but high agency people are able to go farther than ever before.