Answered raw tape
D 5 · C 5 · P 4 · Cm 4 4.60
Q Why do you think it didn't work? Because it, it felt like an awful market.
A It was like a graveyard, like, you know, of all these companies that tried to solve the problem and it didn't. Part of it was just that I think search is a hard problem. In an enterprise, like even getting access to all the data that you want to search, It was such a big problem. In the pre-SaaS world, the, there was no way to sort of go into those data centers, figure out where the servers were, where the storage systems were, try to connect with information in them. It was a big, it was a big challenge. So SaaS actually solved that issue. So like search products, like most of them, most of the companies started in the pre-SaaS world, they failed, uh, because you could just couldn't build a turnkey product. But SaaS actually allowed you to, to actually build something, you know, uh, which is my insight. Was that like, look, you know, the enterprise world has changed. We have these SaaS systems now, and SaaS systems don't have versions. Like everybody, all customers have the same version. You know, they are open, they're interoperable. You can actually hit them with APIs and get all the content. I felt that the biggest problem was actually solved, which was that I could actually easily go and bring all the enterprise information and data in one place, uh, and build this unified search. System on top. So that was actually a big unlock.
AI assessment note: “In the pre-SaaS world, the, there was no way to sort of go into those data centers”
Answered raw tape
D 4 · C 4 · P 3 · Cm 3 3.60
Q Now that you have this sort of Corpus of information, right? You basically aggregated all the internal documents of a company, which in itself is incredibly useful just for search, but you've also got down the route of like enabling applications to be built on top of it in different ways. Can you talk a bit about that and what are some of the common use cases that you're seeing?
A So we started with, you know, this vision of building a Google in your work life, um, but then as models got better, developed like these reasoning and generation capabilities. So first, like, you know, it changed our product and like our new product, like Green Assistant, you know, it sort of looks and feels more like ChatGPT. Um, so instead of like, you know, me going, asking questions and seeing, you know, a bunch of links coming back to me, you know, now of course you converse with Glean, you ask questions, and it works just like Chargibri. You come and ask a question. It's going to actually take all of the world's knowledge, and also additionally, you know, it's going to take all of your internal companies, you know, data and knowledge, and use that in a safe and secure manner, like knowing who you are and what information you can really use within the company to answer questions back for you. So, so that's sort of like the first, um, first progression in terms of our product. Like, you know, we evolved from being a Google to, to, you know, something that looks more like ChatGPT, a more powerful version of ChatGPT inside your company. As you build that, this Glean Assistant actually, you can think of it more like a personal assistant that you're actually giving to every employee in your company. It's a tool, you know, it's your sidekick, you know, it's always available to …
AI assessment note: “our new product, like Green Assistant, you know, it sort of looks and feels more like ChatGPT”
