Sramana Mitra: In building your company, I’d like to understand how you sell. You’re getting leads through different parts of the company, but who buys your product? Is it Head of HR or Head of IT?
Krish Ramineni: Our model is 100% self-service. It could be an individual swiping their card to pay or it could be a team manager. If the department really likes it, their procurement or Head of IT will purchase. We sell to customers the way they want to purchase.>>>
Sramana Mitra: Are you going after enterprises or SMBs? How do you go to market?
Krish Ramineni: It’s a very blended mix. It’s a very interesting challenge and opportunity with product-led growth. Fireflies can be used by one-person SMBs as well as 10,000-strong organizations. Typically, it starts with that one user inside an organization who shows is to the team. We have this bottom-up adoption. What’s that led to is folks reaching out saying, “I’m seeing a bunch of my teammates using this. I would love to learn more. I want to see how we can deploy it for the team.”>>>
Krish discusses how he used completely organic go-to-market strategies to disseminate an AI-intelligent note-taking assistant product.
Sramana Mitra: Let’s start by introducing our audience to you as well as to Fireflies.
Krish Ramineni: The journey goes back a couple of years. When we started Fireflies, our mission was different. We were solving the same problem in the AI space, which was around understanding conversations and deriving meaning from those conversations. The platforms that we were doing this on were different. Today, Fireflies is an AI meeting assistant that joins meetings and transcribes it, generating notes and summaries.>>>
Sramana Mitra: That’s still a horizontal issue though. Connectors are still horizontal plumbing. There are a finite set of data warehouse that you need to connect to. As long as you have those, you are good. Where is the vertical logic coming from?
Nitesh Chawla: Then we got through mapping workshops. We sit down with the business person and go through the process of understanding the business question, looking at the data, and doing some validation. We conduct workshops. We have deep domain knowledge of the banking sector now. I was always convinced it’s a collaboration. It’s an immersion process. Then we bring in that vertical knowledge into our technology layer.>>>
Sramana Mitra: The main question I am asking is at what point did you start productizing?
Nitesh Chawla: We started thinking about it from a services perspective. One thing that’s true today is that in the mid-market, you must have a partnership services model attached to it. It needs human expertise along the way. Having said that, in about 2013 or 2014, we were doing our first demo of Aunsight 1.0. In 2013, we launched it. We came out with a data platform.>>>
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.>>>
Sramana Mitra: How much seed funding did you get?
Nitesh Chawla: I don’t remember, but it was enough to pay salaries for multiple individuals.
Sramana Mitra: Like in the hundreds of thousands?>>>
Sramana Mitra: What you’re describing is the journey of a lot of techies into entrepreneurship as well. It’s not about technology looking for a problem to solve. It’s about identifying the problem and then figuring out how to solve that problem using technology. In AI, this is a major issue.
Nitesh Chawla: It truly is.
Sramana Mitra: This is why domain knowledge is important. It’s very difficult for AI experts to come up with a problem to solve. They know the technology side of it. They don’t really know what the problems are. We’re seeing this massive interest in the AI segment now for people who have domain expertise.>>>