CTGT, a company that is enabling enterprises to scale their AI efforts with a new approach to customizing, training, and deploying AI models that is up to 500 times faster, announced that it has raised an oversubscribed $7.2 million seed round to accelerate product development and sales and marketing.
Gradient (Google’s early-stage AI fund) led the funding round with participation from General Catalyst, Y Combinator, Liquid 2, Deepwater and notable angels including François Chollet (Google, creator of Keras), Michael Seibel (Y Combinator, co-founder Twitch), Paul Graham (Y Combinator), Peter Wang (co-founder Anaconda), Wes McKinney (creator of Pandas), Mike Knoop (co-founder Zapier), Kulveer Tagger (Zeus Living), Andrew Miklas (co-founder PagerDuty) and Taner Halicioglu (first full-time Facebook employee).
With enterprises looking to move their AI projects from proof-of-concept to production at scale and move from low-risk use cases like chatbots to high-risk ones like security, the limits of AI computing have become apparent. AI requires enormous (and growing) amounts of compute and energy. Model developers speak of AI hitting the wall on compute, limiting what AI can do.
CTGT co-founder & CEO Cyril Gorlla has been thinking about this challenge for years and made it the focus of his research for his endowed chair at the University of California at San Diego. In 2023, he published a paper on the topic (presented at ICLR) that described a new way of evaluating and training AI models that was up to 500 times faster and resulted in three nines of accuracy – a huge leap over current methods. That methodology became the basis for CTGT.
Even though many other vendors can identify model problems, only CTGT can automatically refine and retrain models on the fly in production environments – eliminating the need to take models offline for updates.
Enterprises can utilize CTGT to ensure that AI models perform in line with their policies, including privacy, security and corporate standards guidelines – even as environments change. CTGT can help companies respond to changes in customer demand by giving models more autonomy or being more restrictive to security issues when new threats emerge.
For example, if an enterprise faced an emerging online security threat such as a prompt engineering attack, CTGT could recognize that and adjust a model on the fly to resist the attack. CTGT can also detect and fix hallucinations, inaccuracy and data leakage.
Launched in mid-2024 by Gorlla and co-founder Trevor Tuttle, CTGT is already working with a Fortune 10 company to deploy safe, on-device AI, and has landed enterprise customers who are already relying on CTGT software to close the gaps between AI safety and deployment.
One of CTGT’s first customers is Ebrada Financial, which utilized CTGT to improve factual accuracy of its frontline customer service chatbots.
KEY QUOTES:
“CTGT’s launch is timely as the industry struggles with how to scale AI within the current confines of computing limits. CTGT removes those limits, enabling companies to rapidly scale their AI deployments and run advanced AI models on devices like smartphones. This technology is critical to the success of high-stakes AI deployments at large enterprises.”
- Darian Shirazi, Managing Partner at Gradient
“The lack of certainty and trust in models’ output is a significant barrier to adoption in high-stakes industries like healthcare and finance, where AI can make the biggest difference. By greatly improving accuracy, CTGT is removing that barrier.”
- CTGT co-founder & CEO Cyril Gorlla
“Previously, hallucinations and other errors in chatbot responses drove a high volume of requests for live support agents as customers sought to clarify responses. CTGT has helped improve chatbot accuracy tremendously, eliminating most of those agent requests. We’re very happy with the performance.”
- Ley Ebrada, Founder and Tax Strategist at Ebrada Financial
