TLDR: ran out of runway, stakeholders from clients moving on all at the same time. Longer story: I ran a startup that did natural language data analysis (kinda

TLDR: ran out of runway, stakeholders from clients moving on all at the same time. Longer story: I ran a startup that did natural language data analysis (kinda like what people are trying to do now with ChatGPT). You could ask it a question (via email or command line) and it would return its analysis. It could do a variety of statistical analysis and could explain the results in words (tho not as well as a finetuned ChatGPT could do today). Technically it was strong. And I'd say way ahead of the curve. A few things caused the failure: 1. Spending too much time keeping one potential cash cow instead of finding more clients. Having failed a few prior startups, we (cofounders) were obsessed with getting and more importantly keeping clients. This led us to build integrations for clients. One integration was particularly absurd: the "database" that they wanted to connect to is a PowerPoint file on a SharePoint server. Specifically the tables on particular slides. We spent way too much time building custom integrations 2. Running costs were too high. We had developed a sorta "staggered on-line" training scheme. Each client had its own model. Monthly costs per client reached $2000 per month. But with one of the clients we absorbed the costs because they were a potential cashcow (same client as above) 3. The main stakeholder at this potential cashcow left the company to found his own startup, leaving no one else to advocate for my product. At the same time the two other clients decided it was way too expensive to having not enough of an impact on the business. Thus, we ran out of money. Good news is that Gorgonia (https://github.com/Gorgonia https://github.com/Gorgonia) was born from this. I'm still working on the framework for deep learning today