𝗛𝘆𝗯𝗿𝗶𝗱 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗳𝗼𝗿 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗥𝗔𝗚

𝗛𝘆𝗯𝗿𝗶𝗱 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗳𝗼𝗿 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗥𝗔𝗚

Most first RAG systems follow one path. You embed documents. You embed questions. You retrieve nearest vectors. You put them in a prompt.

This works in demos. It fails in production. Retrieval is the problem.

Vector search finds meaning. It knows "cancel plan" means "stop subscription". But vector search misses exact words.

Enterprise users type specific terms:

• Product codes
• Error strings
• Invoice numbers
• Clause references

Embeddings smooth these details. Embeddings generalize. They do not match exact tokens.

Use hybrid retrieval to fix this.

Source: https://dev.to/rishi_kora/hybrid-retrieval-for-production-rag-bm25-vectors-and-re-ranking-step-by-step-32l4 Optional learning community: https://t.me/GyaanSetuAi