Community Discussions

The TS version of [LlamaIndex](https://saaskart.co/software/llamaindex) is newer than Python. How mature is it for production Node apps, and what features lag b

Documents change constantly. What ingestion and re-indexing patterns keep a [LlamaIndex](https://saaskart.co/software/llamaindex) knowledge base up to date with

Many apps mix databases and documents. How are you using [LlamaIndex](https://saaskart.co/software/llamaindex) to query both SQL and text sources in one workflo

How are people measuring whether their [LlamaIndex](https://saaskart.co/software/llamaindex) retriever is returning the right context? Any evaluation harnesses

At some point self-hosting indexing gets old. What pushed teams to adopt LlamaCloud for [LlamaIndex](https://saaskart.co/software/llamaindex), and was the migra

Beyond RAG, [LlamaIndex](https://saaskart.co/software/llamaindex) has agent tooling. How reliable are its agents for multi-step tasks compared to other framewor

[LlamaIndex](https://saaskart.co/software/llamaindex) supports many vector databases. How did you pick between Qdrant, Weaviate, Chroma, and Pinecone for your w

Chunk size and overlap make or break RAG. What chunking settings in [LlamaIndex](https://saaskart.co/software/llamaindex) gave you the best answer quality?

Complex PDFs wreck naive chunking. Has LlamaParse in [LlamaIndex](https://saaskart.co/software/llamaindex) actually improved retrieval quality on tables and mul

People constantly compare the two. [LlamaIndex](https://saaskart.co/software/llamaindex) leans data and retrieval; LangChain leans orchestration. Where did each

Going from a local Haystack script to [deepset](https://saaskart.co/software/deepset) Cloud should be smooth. What changed in your pipeline definitions during t

Once a RAG app ships on [deepset](https://saaskart.co/software/deepset), how do you keep watching quality? Are people sampling responses or collecting user feed

Both target RAG, but [deepset](https://saaskart.co/software/deepset) leans enterprise platform while LlamaIndex leans framework. Which fit your team's build-vs-

Grounding helps but does not eliminate hallucinations. What pipeline patterns in [deepset](https://saaskart.co/software/deepset) most reduced wrong answers for

RAG can call an LLM on every query. How are teams caching, reranking, or shrinking context in [deepset](https://saaskart.co/software/deepset) to keep costs sane

Dense, sparse, or hybrid retrieval all have trade-offs in [deepset](https://saaskart.co/software/deepset). What has given you the best grounding for your docume

Grounding answers means wiring up documents from many systems. Which connectors and ingestion patterns are working well with [deepset](https://saaskart.co/softw

Being EU-based, [deepset](https://saaskart.co/software/deepset) appeals to GDPR-conscious buyers. How has deployment gone for teams with strict data residency n

Measuring whether retrieval actually improves answers is hard. How are people using [deepset](https://saaskart.co/software/deepset) evaluation tools to catch ba

Haystack is free and open source, so what does [deepset](https://saaskart.co/software/deepset) Cloud add for production RAG? For teams that upgraded, was the ev