Bootstrapping an Artificial Intelligence Startup with Services: Nitesh Chawla, Founder, Aunalytics (Part 4)

Sramana Mitra: The other thing that you said is early validation. If you look at our work, we use different kinds of bootstrapping techniques. One of them is Bootstrapping using Services. What you’re describing is exactly that, which is going to customers and taking services projects with a specific problem domain in mind. Then you productize based on a bunch of projects.

Nitesh Chawla: Yes. You can bleed yourself and take a bunch of capital. Then you’re raising capital and selling what you have built. The second thing that happened was there were a couple of clients who believed in us.

One of them was E.W. Scripps. They had this business intelligence thing that they asked us to present. I didn’t want to do BI stuff, but we still had to present it. I had a ticket. I’m not going to talk about the BI stuff. Anyone can do BI. We wanted to do something more. I walked in with an idea of how we will build the big data product and create an audience engagement framework. Why are my audience coming? What are they seeing? How long are they staying?

That’s what we pitched – a data and digital convergence product. I went in from the left field. I said, “I wouldn’t hire me for the BI stuff. I’ll tell you what I believe we should do. I’ll tell you there’s no product that does this. I’ll also tell you that we can do it if you want to partner with us.” They’ve stayed with us for around nine years now. We also got a couple of banking clients. We said, “Only if you get value will you pay us.” Having real data to build a product on is priceless.

Sramana Mitra: This is one of the problems we deal with all the time in the AI companies. Without a live dataset, you cannot build an AI product. You’re hitting the nail on the head on how do you do an AI company without access to the dataset.

That’s another reason why I like bootstrapping using services for AI companies. You can get access to live datasets.

Nitesh Chawla: That’s what we focused on, which allowed us to show to other banks. We also got a large media company in North Dakota where they were using algorithms to identify which customer is at risk of leaving. They’ve been using our models for the last eight years now.

Sramana Mitra: In the beginning when you were just getting started with these services projects, what was the scale?

Nitesh Chawla: The first year that we did, there were tens of thousands of dollars. The beauty was, we were already at a recurring revenue scale. We were hosting them as well.

Sramana Mitra: They were on a subscription model.

Nitesh Chawla: Yes. That was clear to us as well. It’s not just one-time fees. We have to get it to a recurring revenue. It shows value.

Sramana Mitra: You started in 2011?

Nitesh Chawla: We started talking in 2011. 2012 was when started put some things in. Tracy Graham also recruited a CFO, Jim Fulton, as the President of the company.

Sramana Mitra: It sounds like you did raise money later on.

Nitesh Chawla: We continued to raise money over time. All that money raising has been run directly by Graham Allen.

Sramana Mitra: The first time you raised money, let’s say the Series A, what did you have in place? Did you start moving from services to product? If so, what was the product story?

Nitesh Chawla: I should clarify. We don’t have distinct Series A to C because we have a continuous access to the fund that’s managed by Graham Allen. Graham Allen is a private equity group. We are part of their portfolio. They were raising money. Now we are doing it. Now we are going for a much bigger raise.

This segment is part 4 in the series : Bootstrapping an Artificial Intelligence Startup with Services: Nitesh Chawla, Founder, Aunalytics
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