[eambutu]

In terms of what businesses we're targeting: we wanted to provide either 1.) a turnkey solution for a company GPT for all the people who don't have it yet, or 2.) a higher quality company GPT for people who do have an internal solution.

Our sense is that ~70% knowledge companies at large still don't have a custom GPT yet, and that of the people who do, our system can be more performant because we're spending more effort than their internal team is. There's a lot of details we've solved on data ingestion and search algo that improved our accuracy dramatically, and things breadth of data connectors is the kind of thing that is expensive for an internal team but worth it if you're providing the service at large.

Not sure what you mean by "data seems to be stored outside of the customers control," but fortunately I think many SaaS apps that were trying to lock down customer data from themselves are walking that back a little bit.

[Ucalegon]

Please look into the Zero Data Retention policies of the subprocessors that you are using. For example, Open AI does not include files as falling under their ZDR [1], thus utilizing OAI as an LLM solution inherently adds unnecessary risk of data exposure that many enterprise clients do no want to onboard. Also, you have to think about those companies obligation to their clients/customers when it comes to data security, along with the risk of IP being exposed to 3rd party systems that they do not have control over, when they make their decisions when it comes to utilizing various business solutions.

[1] https://platform.openai.com/docs/guides/your-data#zero-data-...