We're an open CORE (caps for emphasis) deep tech company YC has funded in the deep learning space.
We have proprietary software we sell as well as helping people go closer to the applications. We spend a lot of time on relationships with fortune 2000 vendors with existing channels for distribution.
As the CTO of a startup like this I spend my time on coding, leading an engineering team, and managing partnerships with technology companies that help us sell an integrated solution.
We focus on the fortune 2000. One of the things that concerns me is: "My startup bought a support contract from rethinkdb"
No offense to the founders of either, but usually such things are in the 6 figure category or later and require something larger than what a startup can pay.
Selling a cloud version which is easier to scale with more users and less costly on the engagement side (vs say: high touch enterprise) may have been a problem with the business model.
Other plays in the space (maybe gitlab can comment here) tend to minimize support costs to make it easier to work with smaller entities. This may work for data base companies and I hope this is not interpreted as "what I'm saying works for everyone"
What we're doing by default requires some high touch and what might essentially be touching more sensitive problems with a wider variety of applications.
Where deep learning and databases line up is the wide applicability of problems and data types vs say: source control which I won't comment on here (due to lacking knowledge in the space beyond being a user)
My cofounder and I met slava when we were in YC and I have to say we learned a lot from him. He clearly had experience in the space. This space is definitely hard though. I wish them and their community the best no matter what.
Focusing on the customer base from day 1 here is definitely a must.
One of the distinct things we do (other open source startups do this) is figure out which features belong in an enterprise version and a community version.
You can't be everything to everyone and every feature has a price. Boiling the ocean will kill you here. A lot of the engineering team's job is to figure out ROI for certain kinds of features and what kind of problem the feature solves "community" vs "enterprise". It sounds like the enterprise version started later which is a shame. I can say for us, community feedback has been crucial and quick feedback loops help keep us tied to real problems. There's always a certain ratio of engineering time spend on customer problems vs "core features everyone can use". I think a lot of startups have to measure those trade offs.