Pinecone is a vector database service for storing embeddings and finding the most similar items fast, often used to give AI apps the right documents.
In plain words
AI apps turn text or images into embeddings, lists of numbers where similar meanings end up close together. Pinecone stores those numbers in an index and, given a query, returns the closest records. It also supports keyword search and filtering by metadata, and handles the complex indexing decisions behind the scenes, including in a serverless setup.
A quick example
Imagine a help centre with thousands of articles. Each article is turned into an embedding and saved in Pinecone. When a customer asks a question, the app embeds the question, asks Pinecone for the closest articles, and hands them to a language model to write the answer.
Where you'll meet it
- Retrieval for RAG chatbots.
- Semantic search and recommendations.
Related
Sources
- DocsWhat is a Vector Database & How Does it Work?, Pinecone · read 29 Sept 2026
- DocsIndex data overview, Pinecone Docs · read 29 Sept 2026
Checked by WhatIsAI against the sources above · 29 Sept 2026. Spotted an error? Report it.