LiquidIndex - Implement RAG in Minutes - Fast, Simple, and Scalable
Setting up a RAG pipeline shouldn’t take hours. LiquidIndex makes it dead simple—just plug in your own data and query it instantly with our API. No complex setup, no headache. Perfect for devs who want AI-powered search without the hassle.
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Buildspace fellow here. Here supporting builders.
What type of RAG pipeline or type of RAG did you implement?
@tomas_baron Hey! Thanks for stopping by! Currently, it is a straightforward RAG implementation, which LlamaIndex refers to as 'naive RAG.' Documents are chunked and stored in a vector database for retrieval, so nothing fancy just yet. I wanted to flesh out the system first before adding more advanced retrieval techniques. I would love to hear your thoughts on LiquidIndex. Do you have any suggestions or features you would like to see?
@tomas_baron @karthik_kandikonda Great starting point - checkout GraphRAG and LightRAG (for better scores)
@tomas_baron @aiparth Will do! I was thinking of letting users select the type of RAG and their preferred vector database when creating a project. What are your thoughts on that? Or do you think there are other features that should take priority?
Thank you very much for the feedback and support!
This is awesome! I really liked this demo and how seamless the process is. I will be following this to see where it goes in the future.
@alex_w5 Thank you very much!
Clean interface, def looking forward to see where this progresses and will keep tabs on yall. S5 LFG!
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wow actually just made the account and love the ui/ux def def bookmarking now. I just did the testing. If anyone hasn't yet yall should def sign up.
@e_bbb Thank you so much!!! Do you have features you'd like to see implemented?
@karthik_kandikonda not atm but will stay posted and let ya know
Hey Product Hunt! 🚀
I'm super excited to be launching here for the first time! I’ve shared this project a couple of times on X (Twitter), but some friends told me about Product Hunt, so here I am!
I started working on this back in October 2024 because I saw the potential in cloud-based RAG—but most tools I found were either too complex, didn’t integrate well with other systems, or required too much setup. And honestly, why should you spend extra time building RAG when you could be focusing on your actual product?
That’s why I built this—to give developers high-quality AI search that just works, so they can spend more time building and less time side questing.
With this launch, you can:
✅ Upload and connect your documents via file upload (Google Drive support is pending approval)
✅ Query across ALL your data effortlessly— with just one API call
✅ Get direct sources for every response, so you know exactly where the information came from
This is just the beginning, and I’d love to hear your thoughts! Your feedback means the world to me, and I can't wait to see how people use this.
Would love to know—what’s your biggest frustration when working with document-based AI?
Thanks for checking it out! 🚀