Building an AI Unicorn: Glean CEO Arvind Jain (Part 1)

Arvind is an experienced entrepreneur who was able to raise $15M on a concept to solve a big problem. Since then, Glean has been abundantly funded, generates abundant revenue and has become a legitimate Unicorn.

Sramana Mitra: Let’s start at the very beginning of your journey. Where are you from? Where were you born and raised? What kind of background?

Arvind Jain: I was born in Jaipur. That’s where I grew up. From there, I went to college in Delhi. I attended IIT Delhi. Then from there, I came to the States. I’ve been here since then.

Sramana Mitra: What year did you come to the States?

Arvind Jain: 1996.

Sramana Mitra: What did you do?

Arvind Jain: I joined a PhD program in Computer Science at the University of Washington. I didn’t complete that.

Sramana Mitra: I joined the PhD program at MIT in Computer Science. I did not complete it because I went to start a company. When you left University of Washington, what did you leave it for?

Arvind Jain: I went to work for Microsoft. I spent a couple of years there. From there, I jumped into a startup. I joined an early-stage company called Akamai. It started out of MIT. Then I joined Riverbed after that. Then I joined Google. It was still a privately-held company. It was still small. I spent over a decade working on search.

Sramana Mitra: Based in Mountain View?

Arvind Jain: Yes. I did spend a couple of years in Google India. I helped start the operations in Bangalore and built an R&D team. I spent most of my time in Mountain View. 2014 was when we started Rubrics. It’s large now. Then in 2019, we started Glean.

Sramana Mitra: What is the thesis of Glean?

Arvind Jain: Think of Glean as a Google or ChatGPT for your company. It makes it easy for people to find institutional knowledge. Rubrics had more than a thousand people. We grew fast because we had a product that businesses needed. That growth came with a lot of pain. Particularly, productivity of employees started to go down. Getting them up to speed was hard.

We didn’t know what the problem was. In an effort to learn what was wrong, we did surveys. The biggest problem was people not knowing where to ask for things or who to ask for help. If you think about enterprises today and the world we live in, there’s lots of knowledge that keeps growing every day.

Second, a lot of enterprise knowledge has gotten fragmented. If you’re using Google, you probably store a lot of your knowledge on Google Drive. It’s hard to remember where the information is. I was also finding it hard to find things. I’m a search engineer. There was no product for our problem.

This segment is part 1 in the series : Building an AI Unicorn: Glean CEO Arvind Jain
1 2 3 4 5 6 7