Ted Gaubert

Background

About Ted Gaubert

Ted Gaubert serves as Chief Technology Officer at Graphite. Prior to Graphite, he was Chief Technology Officer at Dun & Bradstreet (NYSE: DNB), a leading provider of data, analytics, SaaS, and API products. His engineering teams were responsible for 30+ SaaS products {FinTech, Sales, Marketing, Data Management, Risk, Credit and Compliance} which generated over $1.5B in annual revenue. He personally invented and patented three artificial intelligence technologies as well as leading technology innovation across the portfolio. Prior to D&B, he founded Noodle.ai, one of the first pure play artificial intelligence companies. Dr. Gaubert is credited with coining and trademarking Enterprise AI™ as well as defining Enterprise AI™ as a market category. He grew the company’s valuation from $0 to $300M+. The company won awards such as Top 10 companies to work for (LinkedIn), Forbes Top 50 "Most promising AI Companies", and Intel Partner of the Year 2020. His work on inventing Enterprise AI™ technologies rocketing the company's growth with headcount growing by 250% in the first 24 months. He attracted $70M+ in external capital investments including TPG Capital, Dell Technologies, Mitsubishi, SMS and others. Prior to Noodle.ai, he was CTO at Infosys Consulting and helped grow revenue to $800M. That venture was later merged into Infosys (NYSE: INFY) Worldwide Consulting & Systems Integration (C & SI), which resulted in a growing business unit of over employees and $2.5B in annual revenue. C & SI was later refocused into management consulting services (MCS) as "Tip of the Spear" for Infosys. When he left, Infosys was over employees and had a market cap of $40B. Ted is a globally recognized technology thought leader, innovator, and disruptor. He is one of the handful of selected executives in the official LinkedIn Influencer program with followers. Expertise: AI, Machine Learning (ML), Natural Language Processing (NLP), NLU, NLG, GAN, knowledge graphs (KG), RDF, SPARQL, ontology, neural networks, large language models (LLM), CNN, DNN, LSTM, Transformers, BERT, GPT, Deep Learning