[Weves]

"We were building something similar in house, but then we found Danswer". That's something we keep hearing all the time :D

(1) We handle chunking, embedding, building the keyword search index, etc. all on our end! We use Vespa as both our Vector DB / Search Engine (it allows a custom hybrid search, which we've found to perform really well). So no, you would not need to bring your own Vector DB - everything needed to run the system is managed dockerized and managed by Docker compose / kubernetes (whichever you choose).

(2) It would be straightforward! We both offer an API to ingest documents into the system as well as a pretty simple connector interface that you can implement to add your own custom connector (https://github.com/danswer-ai/danswer/blob/main/backend/dans...)

[timby]

My only other concern is we want to control role based access, so our users can login with org Azure AD accounts. And we want have project / document context lens for the AI chatbot which are available only to specified users.

[Weves]

We do have support for IdPs like Azure AD + role based access control (these aren't in the MIT version of Danswer though :sweat:).

If you're interested in learning more, would love to chat through the details on Slack / Discord.

[timby]

Wow! you jumped onto those questions before I read more and deleted them. Thanks :)