Pinecone Newsroom

With Pinecone Local, you can now prototype, test, and develop AI applications locally while seamlessly integrating workflow testing into CI/CD pipelines.

Announcing expanded inference capabilities alongside our core vector database to make it even easier and faster to build high-quality, knowledgeable AI applications with Pinecone.

A deep dive into how Pinecone supports two new security features, 1) Customer-managed encryption keys (CMEK) and 2) Role-Based Access Control (RBAC) with API key roles

Enhancing retrieval augmented generation (RAG) and enterprise search with pinecone-rerank-v0

New cascading retrieval capabilities make it seamless to combine dense retrieval and sparse retrieval and reranking into a unified search pipeline, delivering unparalleled precision, performance, and ease of use.

How to use Pinecone Assistant to accelerate businesses that build RAG systems. Case study AI RAG

At Microsoft Ignite, Microsoft announced that Pinecone is one of their first GenAI Azure Native Integration partners. This follows their recent announcement at GitHub Universe of Pinecone as one of the providers in their new AI App Template Gallery. Why is this great news? In short, both of those updates mean it’s easier than ever for developers to build with Pinecone on Azure.

We've updated our Datadog integration and Prometheus endpoints for expanded performance and usage monitoring.

In September Pinecone serverless added an evaluation API to evaluate RAG and the ability to choose the LLM, among other updates.

Introducing the ability to bulk import from object storage for Pinecone’s serverless infrastructure. This new capability makes ingesting large amounts of data more efficient for developers building accurate, secure, and scalable AI applications.