Ankur Goyal: belief

Transcript context

…using the product every day. Just to not bury the lead, the logos are Instacart, Stripe, Zapier, Airtable, Notion, Replit, Brex, Versa, Alcota, and the browser company of New York. I don't want to jump the gun to Braintrust. I don't think you've actually told the Impira acquisition story publicly that I can tell. It's on the surface. I think I first met you slightly before the acquisition. I was like, what the hell is Figma acquiring this kind of company? You're not a design tool. Any details you can share? I would say the super candid thing that we realized, just for timing context, I probably personally realized this during the summer of 2022 and then the acquisition happened in December of 2022. Just for temporal context, NTT came out in November of 2022. At Impira, I think our primary technical advantage was the fact that if you were extracting data from PDF documents, which ended up being the flavor of unstructured data that we focused on, back then you had to assemble thousands of examples of a particular type of document to get a deep neural network to learn how to extract data from it accurately. We had figured out how to make that really small, maybe two or three examples through a variety of old-school ML techniques and maybe some fancy deep learning stuff. But we had this really cool technology that we were proud of. It was actually primarily computer vision-based because at that time, computer vision was a more mature field. If you think of a document as one-part visual signals and one-part text signals, the visual signals were more readily available to extract information from. What happened is text starting with BERT and then accelerating through and including chat GPT just totally cannibalized that. I remember I was in New York and I was playing with BERT on HuggingFace, which had made it really easy at that point to actually do that. They had this little square in the right-hand panel of a model. I just started copy-pasting documents into a question-answering fine-tune using BERT and seeing whether it could extract the invoice number and this other stuff. I was somewhat mind-boggled by how often it would get it right. That was really scary. Hang on, this is a vision-based BERT? Nope. So this was raw PDF…

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