CTGT

We're building the future of trustworthy AI deployment. CTGT helps enterprises eliminate hallucinations and unwanted behavior in LLMs while dramatically accelerating time-to-production.

Utilizing CTGT's Platform for Model Evaluation and Monitoring 🚀 - Watch Video

The Problem: “Black Box” of AI

The status quo of deep learning involves throwing more compute at models with the expectation that they will achieve true intelligence. The questionable nature of this assumption aside, this will certainly lead to more complex models that we don’t meaningfully understand.

I’ve been obsessed with AI and its potential to change the world since I was a kid. In high school, I took apart old laptops to eke out just a bit more performance to train models, so I’m exceedingly aware how important access to and understanding AI is. (For more background, check out the great piece TechCrunch did on us.)

Enterprise companies are sitting on powerful AI models but can't deploy them due to hallucinations and unpredictable behavior.

• Healthcare providers can't risk medical chatbots giving dangerous advice
• Financial firms need guarantees their AI won't recommend fraudulent investments
• Tech companies need AI that consistently aligns with their brand voice

Our Solution: Principled AI Development

CTGT takes a fundamentally different approach. Rather than black-box approximations, we've developed breakthrough technology that understands how neural networks actually learn.

This allows us to:

• Automatically detect and eliminate hallucinations
• Train models 10x faster with 10x less compute
• Give enterprises foundational control over AI behavior

How it works:

Let’s imagine we ask an LLM about cooking food.

I started lunch by simmering water on the stove. I prepared dough for a homemade pizza dish. Using a knife, I sliced fresh tomatoes and cheese. I spread glue on the bread for tomorrow's breakfast. The dough rose in the oven. I brewed tea while stirring the soup with a spoon. A plate was set, and lunch was nearly complete. Every pot and utensil had its place.

We can determine, for example, that pizza and bread is part of the “food” concept in the model, along with other related things in the output.

https://www.youtube.com/watch?v=WSDro9tEz_w 

And we can determine that “glue” shouldn’t be part of this concept.

https://www.youtube.com/watch?v=skW5Z5CPr9o 

Our technology ensures “glue” doesn’t appear in queries regarding food, reducing hallucinations by 80-90%.

https://www.youtube.com/watch?v=sH8x9boOtF4 

Real Results with Fortune 10 Companies

We're already helping major enterprises deploy AI with confidence:

• Removed bias from facial recognition systems in one step
• Eliminated investment advice hallucinations for portfolio managers
• Enabled fraud detection LLMs with precise error identification

The Team

Founded by UCSD researchers pushing the boundaries of AI:

• Cyril Gorlla (CEO): Recipient of the Endowed Chair's Fellowship at UCSD. His work on efficient AI training was invited for presentation at ICLR and his talk at Ai4 was the most attended in its track. He collaborated with Intel on ML telemetry deployed on 8M+ CPUs. He was named one of 12 “2022 Shining Stars” at UCSD and is an Ivory Bridges Fellow and Nordson Leadership Scholar. He was advised by ACM and Amazon Fellow Mikhail Belkin.
• Trevor (CTO): Deep learning researcher focused on high powered distributed ML systems under Hao Zhang, a student of Databricks Founder Ion Stoica, at UCSD.

Why Now

Legacy companies and those without access to massive amounts of compute can greatly benefit from specialized, domain-specific AI. Current LLM interpretability methods are extremely inefficient, effectively rendering them inaccessible to the vast majority of companies. There’s a shift from large foundation models to those tailored to each company’s brand and applications. Our technology enables this future by making state-of-the-art AI accessible without massive compute resources.

Interested in the Next Generation of AI?

Book a meeting at ctgt.ai if you're:

• A regulated enterprise (healthcare/finance etc.) looking to safely deploy AI
• Struggling with LLM hallucinations or slow iteration cycles
• Want to reduce AI compute costs by 10x while improving reliability

Looking For

• Introductions to enterprises bottlenecked by AI trust/reliability issues
• Feedback from companies dealing with hallucination challenges
• Technical talent passionate about principled AI development

Contact: hello@ctgt.ai

The future of AI isn't just bigger models - it's smarter, more efficient ones you can trust. Let's build it together.