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Pinecone is a vector database designed to enable knowledgeable AI by providing scalable, fully managed vector search and retrieval capabilities. It offers fast, production-grade similarity search across billions of vectors, supports embeddings from hosted or customer models, and enables real-time indexing and hybrid retrieval for applications like question answering, recommendation, and RAG workflows. The platform is serverless and integrates with various cloud providers, data sources, and frameworks, aiming for reliable performance, security, and multi-tenant isolation. Based in San Francisco, Pinecone serves enterprises and developers building AI-powered search and knowledge applications.
Storage News Ticker – February 2
How To Build Production-Ready AI Agents With RAG and FastAPI
Data Engineering for the LLM Age
Why Your LLM Bill Is Exploding — and How Semantic Caching Can Cut It by 73%
We Found Eight Attack Vectors Inside AWS Bedrock. Here's What Attackers Can Do with Them
Commvault Partners with Pinecone, Fortifying Enterprise AI Stacks Against Emerging Threats
Postgres Extension Complements Pgvector for Performance and Scale
Pinecone Matches INIBOX: The Ultimate Guide to High-Performance Mining
MOORES LAB AI Expands Advisory Board with Industry Luminaries
AI Is Breaking the Recipe Blog Model. AllSpice Thinks It Can Also Save It
Show HN: Pinecone Explorer – Desktop GUI for the Pinecone Vector Database
From Shiny Object to Sober Reality: The Vector Database Story, Two Years Later
Leading AI Companies Keep Leaking Their Own Information on GitHub
Endee.io Open Sources Its High-Performance Vector Database for Scalable AI
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