Data indexing

Organizing data for efficient retrieval, enabling rapid access to information in databases, search engines, and retrieval-augmented-generation-rag systems. Critical for reducing latency and improving accuracy in information retrieval.

Key techniques

• LLM-enhanced indexing: Using large-language-models to create semantic indexes (beyond keyword matching), improving recall in RAG systems (e.g., boosting recall from 50-60% to 95% by generating context-aware index representations).
• Structured query generation: LLMs transforming natural language queries into optimized, structured formats for precise matching against indexed data.
• Hybrid indexing: Combining traditional vector indexes with metadata tagging for multi-dimensional retrieval (e.g., filtering by document type + semantic relevance).

Related concepts

• Vector Indexing
• Embedding
• Information Retrieval
• retrieval-augmented-generation-rag

2026 04 14 Improving RAG accuracy for retrieval

Source Notes

• 2026-04-23: Clip source: Project Management Methodologies: 12 Best Frameworks 2025 • Asana # Project management methodologies: 12 popular frameworks Team Asana February 7th, 20258 min r (Project management methodologies: 12 popular frameworks)
• 2026-04-14: # Improving RAG accuracy for retrieval --- --- https://www.youtube.com/watch?v=smGbeghV1JE This video details how a client project successfully improved the recall of its Retrieval-Augmented Generation (RAG) system from 50-60% to over 9 (Improving RAG accuracy for retrieval)