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Pinecone

Pinecone Assistant: A Managed Knowledge Layer for Production AI Applications Multi-domain RAG in n8n: why one knowledge base is not enough Allspice Transforms the Culinary Experience with Semantic Search Powered by Pinecone | Pinecone Building RAG workflows in n8n: choosing the right Pinecone node Knowledge needs a meta-knowledge layer Garbage Day: How Pinecone Safely Deletes Billions of Objects at Scale When "Performance" Means Two Different Things Pinecone BYOC: Pinecone in your AWS, GCP, or Azure account, no vendor access True, Relevant, and Wrong: The Applicability Problem in RAG Use the Pinecone Plugin for Claude Code to develop AI Applications Faster Millions at Stake: How Melange's High-Recall Retrieval Prevents Litigation Collapse Powering High-stakes Patent Search at Scale: How Melange Built a Reliable AI System on Pinecone | Pinecone Pinecone Assistant Node in n8n: Turn Any Data Source Into Knowledge RAG with Access Control Pinecone Dedicated Read Nodes are now in Public Preview Inside Pinecone: Slab Architecture New Bulk Data Operations: Update, Delete, and Fetch by Metadata The Hidden Cost of Building: Lessons from Aquant Simplifying Vector Embeddings with Pinecone Integrated Inference Capabilities Pinecone joins Microsoft Marketplace as a Launch Partner GTM Engineering: Clay + Pinecone for AI-powered Sales Outbound Build an AI knowledge assistant with Google Docs and Pinecone Moving Pinecone forward with Ash Ashutosh as CEO and Edo spearheading our growing AI ambitions as Chief Scientist Pinecone Founder Edo Liberty to Spearhead Pinecone’s Growing AI Ambitions; Appoints Ash Ashutosh as CEO to Expand Vector Database Market Leadership Fast, Accurate Retrieval for Creators at Scale: Delphi’s Path Toward a Million Conversational Agents with Pinecone | Pinecone Announcing Pinecone Pioneers: A Program for Builders, Organizers, and Community Leaders What is Context Engineering? Chunking Strategies for LLM Applications Beyond the hype: Why RAG remains essential for modern AI Obviant Makes 30% More Accurate Defense Acquisition Recommendations Combining Sparse and Dense Retrieval with Pinecone | Pinecone
September 2024 Product Update
Rick Jacobs · 2024-10-01 · via Pinecone

Here’s a rundown of our major releases in September, and where to read more about them.

Evaluate RAG Correctness

The new Evaluation API helps evaluate the correctness and completeness of responses from Retrieval-Augmented Generation (RAG) systems. It’s currently in public preview, and comes built into our Assistant.

Choose the Model for Pinecone Assistant

Pinecone Assistant now allows users to select a specific Large Language Model (LLM) for their assistant, giving developers greater control over the assistant’s responses. Additionally, you can now filter the assistant’s responses based on metadata, enabling more refined and tailored interactions.

Marketplace Billing Integration with All Major Clouds

You can now connect your Pinecone organization to the AWS Marketplace, GCP Marketplace, or Azure Marketplace Marketplace for seamless billing integration. This makes it easier to manage subscriptions and optimize costs through your preferred cloud provider.

Additional Integration Guides for Data Pipelines

New integration guides for Datavolo and Matillion can help you get started composing your data pipelines quickly and easily

Check out the release notes for a running list of all product and feature releases. If you’re new to Pinecone, try it out for free today.