This is often the move when the team's spent the money developing something and now the end's in sight, so they want the chance to leave and take the code with them.

Don't know if this is that at all, but it's always worth considering.

That is almost certainly what’s happening here. They raised $3M three years ago, at the peak of evaluations, and don’t have the metrics to raise a Series A in the current climate. Running out of money and want to leave some artifact behind. A very difficult and emotional transition.

I don't understand the "leave the code with them" part

I think they mean by open sourcing, they can take the code to a new startup without having IP legality issues.

Would open sourcing the core IP of a company “typically” require board approval?

If a company goes under, the investors will want to sell off the IP, open sourcing everything would make that IP less valueable. There must be some blanket clause in the term sheet to cover that, right? Ie: founders won’t do anything which will materially hurt the company without board approval (or something, I am no where close to a lawyer, this is all conjecture)

If it mattered it would have become part of VC contracts years ago.

Early stage VCs make money on the big winners, not on the tail end of companies that don’t exit for 100x. For the most part, except for patents the IP is worth less than the Aeron chairs at the end.

> Would open sourcing the core IP of a company “typically” require board approval?

At this stage, if they can't raise a series A I'd assume they still have a majority of the "board" to themselves.

You can look at the history of Erlang for a similar example. A very crude summary could be that Ericsson developed the language, took it to production, and then they decided to replace it with Java. The people that did the language design convinced management to release Erlang and the VM as FOSS, and then they promptly went and started a company that could use the tooling they'd developed.

I'm aware I'm leaving out a lot of detail, but it's not clear to me what has become public knowledge and what has not and I happen to know some people that were involved.

getting into enterprise is hard, so probably trying open source to help with that.

Enterprises are spending lots of time and money on this. The biggest issue that has slowed down sales cycle at this stage has been data governance. Most folks think it’s about accuracy or latency (which of course is an issue) but data governance can make this whole thing a non starter.

Can you explain more about why governance is the issue with a service like this? Companies not wanting their data to go off prem?

yes. some want BYOC solutions. others don't want to even be perceived as being used to train an LLM. not to mention CCPA, GDPR, etc etc etc.

lots of questions around what data is being sent to the LLM, or just schema.

Interesting. So by open sourcing you think companies can self host and it negates some of these issues? Or is your goal into increase future contributions to keep the project alive and developing?

What % of the NL -> SQL problem is solved in the current version? Ie is this something ready for some type of prod work now, or is it “in 2-3 years we’ll be there”?

Not OP, but there was an EHR SaaS company on HN a day or two back with a similar proposition: it’s open source, so it can be independently verified from a security perspective. It was interesting to me because the code was unusable to normal folks, and even other companies - one of the founders described their moat being the trouble of actually integrating with the ecosystem, and weren’t worried about competitors using it. It really hammered home to me how open source is more and more a marketing lever lately.

There are organizations using Dataherald in production right now.

The latency is ~20-30s and it takes some set up, so as long as those are not blockers it can be used in prod.

For companies that are willing to put in some effort, the self hosting option is a great one. There are certain use cases where this works now, and is already in production. These tend to be use cases with some constraints and don’t deal with very sensitive data.