Nice to see yet another open source approach to LLM/RAG. For those who do not want to meddle with the complexity of do-it-youself, Vectara (https://vectara.com) provides a RAG-as-a-service approach - pretty helpful if you want to stay away from having to worry about all the details, scalability, security, etc - and just focus on building your RAG application.
Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
111–120 of 134 posts
Re: Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
#112I have just set this up, pointed it at a internal Google Sites-based knowledge base, and made it available to my team through a Slack bot. It's really nice and easy to get started with and I love the self-hosting support.
Re: Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
#113How do you prevent "how much do my colleagues make?" questions from being answered to the wrong people? I know you mention citations and the ability to backtrack a "fact" to the source document. How robust is this?
So we're leaning on access control to do this! Right now we support manually configured group-based access at the connector level (e.g. Users X, Y, and Z make up the `Engineering` group and that group should have access to Folders A, B, C in Google Drive + Github). We're also in the process of adding the ability to sync permissions from sources. For example, with this in place you would only be able to chat with / se…
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Re: Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
#114Won't it be better to transform documents into Q&A style instead of "chunking"?
Re: Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
#115Good luck folks! I'm glad there are projects trying to solve enterprise search. I guess the main problem is the "private" aspect, if I've understood your goals correctly. Since most SaaS products lock down the private data unless you pay enterprise fees for compliance tooling. For instance, if you want to ingest data from private Slack channels or Notion groups, you have to get the users in those groups to add your b…
I think search is the wrong lens to look at it. Yes, finding relevant information quickly is important, but the key to enterprise search tools would be to get a holistic view around any topic. A typical enterprise has a lot of silos (12 out of top 15 enterprise apps on G2 are addressing this problem) and the flow of information doesn't exist. Any enterprise search tool helps in aggregation and triangulation of conver…
>> the hard part is contextualizing it in a way it is immediately useful. That depends on understanding the company/domain lingo, understanding users, etc.
How do you control this deterministically? It sounds like the "hard part" is variation in prompting & selectively choosing the right data to include, both of which I could see being good enough right now but hard to deliver definitively.
Re: Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
#116Congrats on the launch! Finally got some time to try this out.
Tried this on a couple of personal documents and compared to asking on
chatGPT (both 4 and 3.5), so far the results weren't great.
For context, the questions needed a little inference and danswer said the info isn't present in the document versus chatGPT which inferred the answer from a related statement.
I do intend to perform a much bigger test around documents but curious to hear thoughts on why this might be the case.
Re: Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
#117Just wanted to drop in and share some love for Danswer. We've been using it as our go-to doc repository for a bit now, and it's been a game-changer for us. Not naming names, but let's just say it's powering some pretty key projects.
What really blows my mind is the LLM capabilities. We're pulling out some seriously amazing answers from our knowledge base, making info retrieval a breeze. And yeah, I've been hands-on with it for the last 3 months, even tinkered around developing some custom connectors. It's been a fun ride.
The team behind it? Absolute champs. Super responsive, and the product itself is rock solid. It's not every day you come across a tool that genuinely makes your workflow smoother and smarter. I've discovered thanks to them also Vespa, and it's our Embeddings de facto DB now.
Big shoutout to the Danswer team. Keep up the awesome work!
Re: Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
#118How does this compare to simply rolling your own OpenAI Assistant (apart from direct integration of Slack etc.)?
So one of the main things we do is automatically sync-ing documents from different sources of knowledge from your team. So all of the data connectors as well as the user authentication and access systems would have to be built from scratch if you did your own. Also if you have more than a few documents you would have to recreate the RAG pipeline (and ours is fairly involved so it would be quite some work). Finally th…
That makes a lot of sense. Thank you!
Re: Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
#119Hello, congratulations. Danswer looks really interesting and the name is simply great.
We are building something similar (internal enterprise search using llm) and I am thinking whether we should jump to Danswer codebase. I would have a couple of questions, if you could answer:
- how would you compare Danswer and privateGPT? Do you see it as a direct competitor?
- you posted below that you have not use llama hub connectors because they do not allow incremental updates? Can you maybe elaborate on that, examples?
- instead of pulling data from different sources, did you consider knowledge graph approach (push) where data and vector index would live together in the single graph database? What would be the advantages of your approach?
- you posted below that you had to implement a custom search. Could that possibly be avoided (with the different architecture?)
Thanks and best
Re: Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
#120Good luck folks! I'm glad there are projects trying to solve enterprise search. I guess the main problem is the "private" aspect, if I've understood your goals correctly. Since most SaaS products lock down the private data unless you pay enterprise fees for compliance tooling. For instance, if you want to ingest data from private Slack channels or Notion groups, you have to get the users in those groups to add your b…
I think search is the wrong lens to look at it. Yes, finding relevant information quickly is important, but the key to enterprise search tools would be to get a holistic view around any topic. A typical enterprise has a lot of silos (12 out of top 15 enterprise apps on G2 are addressing this problem) and the flow of information doesn't exist. Any enterprise search tool helps in aggregation and triangulation of conver…
Exactly, there is a huge amount of value in being able to quickly get a holistic view of topics. Most topics don't exist in an isolated tool - most often there are the official discussions/designs which exist in place, there are customer interactions with the topic which uses a separate channel, and then there are one off small conversations about the topic in chats like Slack. So isolated, tool specific searches are great for finding specific documents, but less useful for getting actionable insights.
Regarding contextualizing: we're currently working on organizational understanding and we're very excited about this one! We're embedding users based on the documents they authored or interacted with, the questions they have asked, description of projects they worked on, and the org chart. The thinking is that, there will always be questions that can't fully be answered via documentation alone. But in those cases we'll be able to recommend someone who might know. It also has the benefit of contextualizing the user asking so that we can surface more relevant results for them.