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From MIT PhD Student to Machine Learning Entrepreneur: CEO Manasi Vartak (Part 4)

Posted on Thursday, Apr 7th 2022

Sramana Mitra: Besides the guy you brought in from Twitter, who else did you bring in as your key team member? How did you find them?

Manasi Vartak: I recruited through normal channels whether it was through Angel List or emailing people. I also started with a small set of contractors overseas. This was after I had some seed money. That gave us a good start. We still work with them.

Sramana Mitra: What kind of functions?

Manasi Vartak: Engineering. It was for building out our commercial features. I couldn’t recruit, fundraise, and code at the same time.

Sramana Mitra: On the sales side, the typical journey of a developer founder is a founder-led sales situation. How long did you do that?

Manasi Vartak: We’re actually hiring our VP of Sales right now.

Sramana Mitra: So you’ve led sales so far.

Manasi Vartak: Yes, it’s a humbling experience. The first few sales calls were people saying no or they just don’t respond. It’s a good reality check. I work with a company called Sweat Equity Ventures. They have an interesting model where they provide services in exchange for equity. I brought them on. I got consultants essentially.

Sramana Mitra: The sales model is outbound?

Manasi Vartak: Right.

Sramana Mitra: You’re going after the head of engineering?

Manasi Vartak: It varies a bit. Teams tend to have different structures. It can be your VP Analytics. Sometimes, it’s your Head of Machine Learning. These can also be IT teams that support data science.

Sramana Mitra: They’re easy to identify on LinkedIn.

Manasi Vartak: I wish it was easier. There are a lot of people with similar titles. This just reflects that ML is an early part of the organization.

Sramana Mitra: You can do that with offshore teams as well. They can do account development and prospect development.

Manasi Vartak: Exactly.

Sramana Mitra: What are the metrics? How many customers do you have?

Manasi Vartak: There are a few case studies on our website that I can talk about. We tend to go after sophisticated midmarket. One of our customers is Scribd. We essentially became their production ML team. They use our system to catalog their models using ModelDB. They package and run them. We monitor them. We get paged if their models go down.

Sramana Mitra: Very good. Your company was pitched as being over $5 million in revenue.

Manasi Vartak: Right.

Sramana Mitra: When did you raise your first round?

Manasi Vartak: That was December 2018. We closed our A round led by Intel Capital. Our seed round was led by General Catalyst.

Sramana Mitra: How much was the Series A?

Manasi Vartak: $10 million. We’ll go up for a B later this year.

Sramana Mitra: Fantastic! Thank you for your time.

This segment is part 4 in the series : From MIT PhD Student to Machine Learning Entrepreneur: CEO Manasi Vartak
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