SF team building the next generation of search

Will Bryk

CEO

Will was one of the first engineers at Cresta where he built real time AI products. He studied CS and physics at Harvard, where he researched human/AI interaction and led the robotics club. Will considers himself an expert in both embedding models and chocolate chip cookies -- the jury is still out on which is more critical for company operations.

Jeff Wang

Co-founder

Jeff spent three years building data and web infra at Plaid. He studied CS and Philosophy at Harvard, where he ran a GPU cluster in his dorm room and was roommates with Will. The team estimates that 20% of social analysis in San Francisco traces back to one of Jeff's many viral tweets.

Ben Chen

Technical Staff

Ben previously did quant trading at SIG and before that took the hardest math course in the country at Harvard. When we find frisbees, tailor made suits, or scribbled math formulas lying around the office, there's usually a Ben behind it.

Hubert Yuan

Technical Staff

Hubert previously worked on projects like particle simulations and automated wheelchairs. He studied CS in the Yao Class at Tsinghua University. Hubert's appetite for clean microservice architecture is perhaps only matched by his appetite for Haribo sour candy.

Shreyas Sreenivas

Technical Staff

Shreyas previously worked on various projects, from training neural networks in Haskell to building a game streaming engine. He studied CS at the University of Waterloo. You can typically find Shreyas analyzing the price/performance of AWS services or crushing the team in basketball, sometimes at the same time.

Eugene Chan

Technical Staff

Eugene previously designed and built LLM products at Palantir. He studied CS at Minerva University. Eugene loves two things and hates one -- designing beautiful frontends, optimizing high performance backends, and eating vegetables.

Michael Fine

Technical Staff

Michael previously worked on ML and privacy at various companies, including Apple. He studied CS at Harvard University. He also somehow finds time to cook chef-level meals and have PhD-level knowledge on nearly everything -- both of which the team enjoys consuming.

Isabelle Hughes

Growth

Isabelle previously was at Mckinsey consulting for tech companies. She studied politics and philosophy at the University of Melbourne. Isabelle has the remarkable ability to work intensely on one screen while at the same time watching a technical lecture on another. The team is unsure whether this comes from McKinsey training or is just an Australian thing.

Vishal Khanna

GTM

Vishal was previously a management consultant at McKinsey & Co., and was part of the strategy team at TikTok Australia. He studied EECS and Finance at Monash University Australia. Vishal is the very rare person who can both code up any product and sell it to anyone. Given his messianic startup skills and obsession with Dune 2, some believe the similarity between 'Vishal' and 'Paul' is more than a coincidence.

What we do

Exa is building web search for AI. Exa’s API lets developers and companies bring the world's knowledge into their AI applications.

Whereas traditional search engines are optimized for human clicks, AI applications need a search engine that’s powerful and precise enough to retrieve hundreds of results with the best information. Exa is the first search engine built for exactly that use case.

Under the hood, Exa trains embedding models, using the same technology behind ChatGPT, to convert web pages into lists of numbers known as embeddings. This technology packs the power of large language models (LLMs) into the search process itself, making search smarter than keyword approaches like Google. Smarter search grounds AI applications in the most relevant world knowledge.

Thousands of companies and developers have integrated Exa, from AI writing assistants helping students cite relevant papers, to VC firms sourcing highly specific startups, to AI research teams at companies like Databricks assembling large, high quality training datasets.

Careers at Exa

Our information ecosystem is broken, and the best way to fix it is to combine LLMs with high quality content from the Internet.

See open roles