
Gemini File Search Turns Multimodal RAG Into a Managed Developer Primitive
Google DeepMind added multimodal retrieval, metadata filtering, and page-level citations to Gemini API File Search.
6 articles

Google DeepMind added multimodal retrieval, metadata filtering, and page-level citations to Gemini API File Search.

Building a RAG system that works in production is harder than it looks. Avoid common mistakes like bad chunking and missing metadata by understanding that RAG is a dynamic system, not just a static database.

A 3,000+ word technical and visionary guide to Context Engineering and Data Molecules. Learn why RAG is no longer enough and how structured data packaging prevents AI hallucinations in production.
Data privacy is the #1 hurdle for enterprise AI. Learn how to architect a production-grade Role-Based RAG system that ensures users only see what they are authorized to access, from ingestion to real-time retrieval.

Does a 2-million-token context window make RAG obsolete? A benchmark study on 'Lost in the Middle' phenomena versus optimized vector search for agentic workflows.

Moving beyond simple vector search. How Agentic RAG uses multi-step reasoning, query decomposition, and corrective feedback to answer complex questions.