We've built a low-code AI agent platform with primary use case in e-commerce (replacing first-line of humans for basic things like product search, QA, etc). It works fairly well if you assemble the script correctly. And if it fails - it just falls back to humans, so customers don't see much difference in their experience.

We're building B2B SaaS that has AI at its core. Some of the customers asked exactly this ("we want your thing to be in house, so that our data never leaves our infra").

The solution is fairly straightforward - prepare custom models that can be deployed on customer side. It is not even something that is hard to achieve with all the great open source models out there. Yes, it's going to be costly, but it can be done.

We've finally managed to close our first customer with our tiny bootstrapped AI sales bots project - so, the only resolution I have for 2024 is to scale that stuff to more customers (never gotten to that stage before, so this is going to be first for me).