[sharp11]

Congrats on the launch! As an iOS dev who dabbles in ML, I'm having trouble understanding what you mean by "data applications" and who this is for. I'm guessing it's targeted at teams that crank out lots of small apps and therefore investment in learning your platform would make sense? It would be helpful if you gave clearer explanation of the use case(s), beyond the generic "customer data platforms, fintech companies building lending and risk engines, and AI companies building prompt engineering pipelines" (which, tbh, means nothing to me).

[cstanley]

Our target audience are data engineers and scientists who are stitching together business apps like CRMs/email marketing tools etc, and building proprietary automations and analytics in between them like generating a customer health score and actioning on it.

One of the problems we’ve intended to solve is the separation of analytical systems (like all your pipelines for counting customers and revenue) and your automations (like do something on customer signup event).

[dang]

That was a good and important question - I've moved cstanley's answer to the top text so other people will get the information sooner. Thanks!