Explosion snags $6M on $120M valuation to expand machine learning platform

Explosion, a company that has combined an open source machine learning library with a set of commercial developer tools, announced a $6 million Series A today on a $120 million valuation. The round was led by SignalFire, and the company reported that today’s investment represents 5% of its value.

Oana Olteanu from SignalFire will be joining the board under the terms of the deal, which includes warrants of $12 million in additional investment at the same price.

“Fundamentally, Explosion is a software company and we build developer tools for AI and machine learning and natural language processing. So our goal is to make developers more productive and more focused on their natural language processing, so basically understanding large volumes of text, and training machine learning models to help with that and automate some processes,” company co-founder and CEO Ines Montani told me.

The company started in 2016 when Montani met her co-founder, Matthew Honnibal in Berlin where he was working on the spaCy open source machine learning library. Since then, that open source project has been downloaded over 40 million times.

In 2017, they added Prodigy, a commercial product for generating data for the machine learning model. “Machine learning is code plus data, so to really get the most out of the technologies you almost always want to train your models and build custom systems because what’s really most valuable are problems that are super specific to you and your business and what you’re trying to find out, and so we saw that the area of creating training data, training these machine learning models, was something that people didn’t pay very much attention to at all,” she said.

The next step is a product called Prodigy Teams, which is a big reason the company is taking on this investment. “Prodigy Teams  is [a hosted service that] adds user management and collaboration features to Prodigy, and you can run it in the cloud without compromising on what people love most about Prodigy, which is the data privacy, so no data ever needs to get seen by our servers,” she said. They do this by letting the data sit on the customer’s private cluster in a private cloud, and then use Prodigy Team’s management features in the public cloud service.

Today, they have 500 companies using Prodigy including Microsoft and Bayer in addition to the huge community of millions of open source users. They’ve built all this with just 6 early employees, a number that has grown to 17 recently and they hope to reach 20 by year’s end.

She believes if you’re thinking too much about diversity in your hiring process, you probably have a problem already. “If you go into hiring and you’re thinking like, oh, how can I make sure that the way I’m hiring is diverse, I think that already shows that there’s maybe a problem,” she said.

“If you have a company, and it’s 50 dudes in their 20s, it’s not surprising that you might have problems attracting people who are not white dudes in their 20s. But in our case, our strategy is to hire good people and good people are often very diverse people, and again if you play by the [startup] playbook, you could be limited in a lot of other ways.”

She said that they have never seen themselves as a traditional startup following some conventional playbook. “We didn’t raise any investment money [until now]. We grew the team organically, and we focused on being profitable and independent [before we got outside investment],” she said.

But more than the money, Montani says that they needed to find an investor that would understand and support the open source side of the business, even while they got capital to expand all parts of the company. “Open source is a community of users, customers and employees. They are real people, and [they are not] pawns in [some] startup game, and it’s not a game. It’s real, and these are real people,” she said.

“They deserve more than just my eyeballs and grand promises. […] And so it’s very important that even if we’re selling a small stake in our company for some capital [to build our next] product [that open source remains at] the core of our company and that’s something we don’t want to compromise on,” Montani said.

Companies betting on data must value people as much as AI

https://ift.tt/eA8V8J Explosion snags $6M on $120M valuation to expand machine learning platform https://ift.tt/3kQrXJV