Introducing integrated inference: Embed, rerank, and retrieve your data with a single API

What this post added

This post announces the General Availability (GA) of integrated inference capabilities for embeddings and reranking, making them accessible via new database endpoints. It introduces new Pinecone models (pinecone-rerank-v0, pinecone-sparse-english-v0) and a Cohere model (cohere-rerank-v3.5) that are fully hosted and managed by Pinecone. The post details how these integrated capabilities simplify AI development by unifying inference, retrieval, and database management, offering seamless scaling and secure networking. It also provides technical details and code examples for using the new features, including creating an index for a specific embedding model using the `create_index_for_model` endpoint and upserting records with the `/records/upsert` endpoint. The post highlights the benefits of combining sparse and dense embeddings for improved search performance and explains the role of reranking in enhancing accuracy and reducing token waste. It also mentions the availability of a new sparse index type in early access.