I'm not familiar with the company but there is serious money in enterprise AI, speaking from experience. These could be very large customers.

Hi,

Yes the deal sizes are mid 6 figures or larger.

We have a larger deal pipeline than that though. A lot more to come :).

Red hat/oracle style on premise (non saas) business model.

We usually target NON computer vison applications like fraud, preventative maintenance in data centers (predicting broken machines) and other mission critical applications.

One example:

http://insights.ubuntu.com/2016/04/25/making-deep-learning-a...

This kind of stuff is a swear word on hacker news but there's actually money in it. Fire away if you have specific questions though :).

What's your strategy to source relatively large deals like that? In general terms. Are you cold calling? conferences? Is it from online advertising? offline? referrals?

Channels based sales and lead gen from conferences.

What sort of value add do you provide on top of what the open source frameworks provide?

Main thing is production deployment software and a service level agreement for models we build.

In machine learning in production there are 2 phases: training and inference (usage)

In training we have spark docker images where you can run cuda right from spark submit.

In inference mode we sit on top of DC/OS by mesosphere embedding lightbend's (they created scala) micrsoservices technology conductr to scale out automatically on a mesos based cluster: http://www.slideshare.net/agibsonccc/deep-learning-in-produc...

Here is more on our enterprise distribution SKIL: http://www.slideshare.net/agibsonccc/skil-dl4j-in-the-wild-m...

If you're curious where the talent is, I cowrote the flagship oreilly book on deeplearning: http://shop.oreilly.com/product/0636920035343.do

We also employ deep learning phds doing everything from deep learning research in health care, ex nvidia, ex cloudera among others.

Enterprise sales are hard.

Indeed but that's what our team can do well. I've never been able to build a consumer product. Enterprise is just about understanding the incentives of the other party and knowing how to navigate the corporate latter.

Probably not a misprint. They could be big enterprise customers.

We don't work with startups :).

I presume you mean "we don't currently work with startups". This is more of a financial issue than an ideological, enterprise only issue, right?

I'm assuming if Grail (http://www.grailbio.com/) who launched in 2016 with $100,000,000 in funding were knocking at your door you would be more than happy to work with them?

Right. Startups typically use python/ruby or commodity hadoop clusters on EMR. It's not an audience match and they don't have a budget anyways.

For anyone else we have a very active open source community: https://gitter.im/deeplearning4j/deeplearning4j

:)

FWIW we spent much of the time building the product and open source community.

Many companies with infrastructure products like ours tend to "incubate" inside a big company first. We chose not to do that. So we spent much of our time just growing the user base first.