[timby]

Great stuff!

I've spent the last 6 months doing fullstack development for a very similar app at my work. Me and the ML engineer on my team are always joking that something like Danswer is going to come around sooner or later to replace what we're building. sad lols

The concept of team-specific knowledge assistants is very hot in our org (which is a gov org). We have HEAPS of legacy and current data that employees and consultants need to comb through to write up documents.

[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 :)