What I’ve learned from building an AI/ML accelerator from the ground up

A startup office. Photo credit: Heisenberg Media

Just a few months ago, we started Zeroth, Asia’s first accelerator for artificial intelligence (AI) and machine learning (ML) startups.

I’m quite experienced with accelerator programs. Before Zeroth, I was at Techstars. First I was in New York and then in London, where I started the first international Techstars program alongside Jon Bradford and Jess Williamson. That experience allowed me to work with over 50 startups, manage over 120 mentors, and hire over 40 Associates and Hackstars.

There, I also got to know other accelerators including: Spark Labs, Startup Wise Guys, 500, Seedcamp, Eleven, ERA, How to Web, ChinaAccelerator, Oxygen, and others.

Over time, I increasingly became interested in AI and ML through my companies, Lingvist and Weave.

However, I couldn’t shake my interest in working with early stage companies, especially those at their very infancy. And that’s when I married these two interests to form a new vision: to deconstruct, fund, and hyper-accelerate the building of AI/ML startups.

Here are some areas every accelerator (or any other investment firm) has to get right.

Brand

Your brand is a precursor to the amount of business you find, your deal flow in other words. If you have a great brand, deal sourcing is improved, you receive more inbound deals, and these deals have more potential for completion.

Coming from Techstars, we didn’t have an issue with our brand. When you’re building an accelerator from scratch, the brand has to be solid.

When you’re building an accelerator from scratch, the brand has to be solid.

An accelerator’s brand is comprised of its portfolio of companies. But without a portfolio to start from, an accelerator has to build its brand on the strength of its team and its connections.

That’s why we assembled one of the best lineups of AI/ML entrepreneurs and venture capitalists.

This included: Jaan Tallinn, cofounder of Skype, Nathan Benaich of Playfair Capital, Frank Meehan of Spark Labs, Jung Hee Ryu of FuturePlay, Daniel Chu from Microsoft Cortana, Thomas Stone from Prediction.io, Azeem Azhar from Exponential View, and others.

In total, this team had worked with companies like Google Deepmind, Siri, Mapillary, Vicarious, Seldon, Weave, and other important AI companies.

Deal sourcing operations

Internal operations

Here are some methods we utilize

Due diligence process