How Often to Reindex, and What Breaks When You Forget
Stale indexes give confident wrong answers. How to set reindexing frequency by document tier, and what breaks when a sync run falls behind.
Reranking Retrieved Passages: The Step Most Teams Skip
Vector search alone buries the right passage at rank 12. See how a cross-encoder reranker reorders retrieved chunks and fixes wrong RAG answers.
Hybrid Retrieval: Combining Keyword Search With Embeddings
Why dense vector search alone fails on company documents, what BM25 still does better, and how hybrid retrieval merges both ranked lists into one.
Vector Database or Plain Keyword Search: When Each One Wins
Keyword search nails exact IDs, vector search handles vocabulary mismatch. A practical guide to picking the right retrieval method for your RAG project.
Choosing an Embedding Model for a Company Knowledge Base
How to pick an embedding model for a company knowledge base: start from your corpus, weigh hosted APIs against self-hosted weights, and measure retrieval.
Build your own AI assistant on your documents
Ragable indexes your files and answers from them, with citations. Start on SaaS or run it on your own infrastructure.
Start from $99/month