Comment by darkteflon

Could you say a few words about why you chose Qdrant for this project? It seems to me there is definitely a place in this space for a back-end focused on retrieval for LLMs that goes beyond simple vector similarity search and encapsulates other metadata creation / indexing and hybrid retrieval techniques to tackle the “false negatives” (missing context) challenge. We’re trying to decide whether leaning on something like Qdrant, Weaviate or Pinecone instead of our current Postgres / pgvector stack might be worth the cost of learning and running extra infra.