Gemini’s Multimodal RAG API is Changing AI Search
Summary
Google updated the Gemini API to support multimodal retrieval, embedding text and images into a shared vector space so users can query mixed-content documents in a single request. The release adds metadata-based filtering and page-level citations to improve precision and traceability for enterprise documents. The article outlines the API pipeline (ingest, chunking, embedding, storing, querying) and highlights use cases in healthcare, engineering and legal. Google also offers flexible pricing with a free tier, free vector storage, and scalable options to accommodate both small teams and large enterprises.
Classifications
industries
HealthTech
applications
Web and Content Management
AskAI Classifications
Labels
SaaS
Consumer Software
Enterprise Software
Linked Companies
Google LLC
$100M to $250M