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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 Build more knowledgeable AI applications with new LLMs and greater control in Pinecone Assistant #NYTECHWEEK 2025 Retrieval-Augmented Generation (RAG) Accurate and Efficient Metadata Filtering in Pinecone’s Serverless Vector Database | Pinecone Terminal X AI Agents, Powered by Pinecone, Turn Complex Financial Data Into Production-grade Insights at Scale | Pinecone Aquant Delivers Scalable, Expert-level Service Intelligence with Pinecone | Pinecone Cascading retrieval with multi-vector representations: balancing efficiency and effectiveness Vector databases aren't just for large-scale enterprise AI Unveiling DIME: Reproducibility, Scalability, and Formal Analysis of Dimension Importance Estimation for Dense Retrieval | Pinecone Fast and Effective Early Termination for Simple Ranking Functions | Pinecone Domain-specific AI Agents at Scale: CustomGPT.ai Serves 10,000+ Customers with Pinecone | Pinecone Using Pinecone asynchronously with FastAPI A Flexible Resource for Top-Weighted Comparisons Between Sets and Rankings | Pinecone Build secure, scalable agentic AI workflows with Rubrik Annapurna and Pinecone Tool up: Pinecone’s first MCP servers are here Add context to your agent with Pinecone Assistant MCP remote server E2Rank: Efficient and Effective Layer-wise Reranking | Pinecone ColBERT-serve: Efficient Multi-Stage Memory-Mapped Scoring | Pinecone Efficient Constant-Space Multi-Vector Retrieval | Pinecone How Vanguard Worked with Pinecone to Boost Customer Support with Faster Calls and 12% More Accurate Responses | Pinecone Pinecone Named to Fast Company's Annual List of the World's Most Innovative Companies of 2025 Launch Week: Pinecone for agents, search, recommendations, and more Optimizing Pinecone for agents (and more) Retrieval Inference for scale and performance How 1up Turns Sales Reps Into Product Experts with Pinecone | Pinecone Don’t be dense: Launching sparse indexes in Pinecone Unlock High-Precision Keyword Search with pinecone-sparse-english-v0 Evolving Pinecone's architecture to meet the demands of Knowledgeable AI Pinpoint references faster with citation highlights in Pinecone Assistant Bringing the leading vector database to your cloud Getting started with llama-text-embed-v2 Natural Language Counterfactual Explanations for Graphs Using Large Language Models | Pinecone Easily build knowledgeable chat and agent-based applications in minutes with Pinecone Assistant, now generally available How to build an agentic, chat or RAG knowledge system using Pinecone Assistant Real-time RAG with Pinecone and Estuary Flow BigQuery to Pinecone in Real-Time with Estuary Flow Stravito Turns Market and Consumer Data Into Actionable Insights with Pinecone Inference | Pinecone Accelerate prototyping and development with Pinecone Local First-of-its-kind Pinecone Knowledge Platform to Power Best-in-class Retrieval for Customers Introducing integrated inference: Embed, rerank, and retrieve your data with a single API Strengthening security and increasing control with CMEK and API key roles Introducing Pinecone Rerank V0 Introducing cascading retrieval: Unifying dense and sparse with reranking From Idea to Action: How Pinecone Assistant Meaningfully Accelerates AI Business Building AI apps on Azure with Pinecone just got a lot easier Building a reliable, curated, and accurate RAG system with Cleanlab and Pinecone Four features of the Assistant API you aren't using - but should Deploying Pinecone with Infrastructure as Code (IaC) Streamlining CI/CD with Pinecone Local September 2024 Product Update Results of the Big ANN: NeurIPS'23 competition | Pinecone Introducing import from object storage for more efficient data transfer to Pinecone serverless Simplify, enhance, and evaluate RAG development with Pinecone Assistant, now in public preview Vectors and Graphs: Better Together August 2024 Product Update Pinecone Helps Deep Talk Deliver World-Class AI Assistants with Lower Engineering Overhead | Pinecone Assembled Delivers Better, Faster AI- Driven Support with Pinecone | Pinecone Llama 3.1 Agent using LangGraph and Ollama Build knowledgeable AI with Pinecone serverless, now generally available on Microsoft Azure Pinecone serverless is now generally available on Google Cloud, adding knowledge to AI assistants and other applications Accelerating Legal Discovery and Analysis with Pinecone and Voyage AI Bridging Dense and Sparse Maximum Inner Product Search | Pinecone Refine Retrieval Quality with Pinecone Rerank Introducing reranking to Pinecone Inference to simplify building accurate AI July 2024 Product Update Connect to Pinecone within your platform to enable a seamless AI development experience Introducing Pinecone API Versioning RAG Brag with Inkeep Co-Founder Nick Gomez LangGraph and Research Agents Introducing Pinecone Inference to streamline your AI workflow
Former Snowflake CEO Bob Muglia and Couchbase CEO Bob Wiederhold Bet on Pinecone
2021-12-16 · via Pinecone

SAN MATEO, California, Dec. 15, 2021 /PRNewswire/ -- Pinecone Systems Inc., a machine learning (ML) and search infrastructure company, today announced that two former CEOs, Bob Muglia (Snowflake) and Bob Wiederhold (Couchbase) joined the company as investors and advisors and are working closely with the company's Founder & CEO, Edo Liberty, to scale the business.

Complex data such as unstructured text documents, call and video transcripts, customer histories, images, and audio is growing. Companies need to search through this data in order to power their search, personalization, and security applications. Yet they struggle to do so, because they are stuck with tooling and infrastructure that was designed for more simple, structured text data.

Companies are increasingly turning to ML representations of complex data, called vector embeddings, to enable searching through that data by semantic meaning. This approach is incompatible with existing databases, and requires a new kind of database that supports vector search at scale. While a handful of hyperscalers have already implemented the technology, most companies don't have the time or resources to build and maintain the necessary infrastructure. Pinecone has built a vector database that makes it easy for everyone else to leverage this state-of-the-art method of searching through complex data.

An enterprise software executive and the former CEO of data warehousing giant, Snowflake, Bob Muglia led the company to five years of unprecedented growth and raised hundreds of millions in funding. Prior to Snowflake he served as one of four Division Presidents at Microsoft managing more than 20% of the company's revenue including server products & cloud services.

"Complex data such as images and video are a potential goldmine of business insight. People can intuitively understand the contents of an image but until the advent of advanced analytics and machine learning, these contents have been opaque to business systems. That has now changed but this requires a new kind of infrastructure that intersects databases and AI" said Bob Muglia. "Pinecone is an innovator and early mover in this space. I believe what they are building is cutting edge today but will become a well-understood standard in this decade."

Bob Wiederhold has more than 25 years of high tech experience, having previously served as CEO of Couchbase, a leader in NoSQL databases, and then its Executive Chairman. From 2002 to 2009, Bob was Chairman and CEO of Transitive, the worldwide leader in cross platform virtualization with over 20M users, where during his tenure the company was acquired by IBM. Until 2001, Bob served as CEO of Tality Corporation, the worldwide leader in electronic design services whose revenues grew to over $200M.

"Hyperscalers such as Google, Microsoft, Facebook, and Amazon invested years in incorporating vector databases and vector search into their applications. They are already seeing improved business outcomes'' said Bob Wiederhold. "The majority of the tech world has either not realized it yet or is struggling to catch up. I'm excited to work with Pinecone on bringing this technology to companies who may lack the time, capital, or bandwidth to build such infrastructures in house."

"Bob Wiederhold and Bob Muglia are the best people in the world to help us scale Pinecone," said Edo Liberty. "Their experiences in shipping delightful products and building great companies map almost exactly to the journey ahead of us. They have already made a huge impact on Pinecone and will undoubtedly continue to do so."

About Pinecone
Pinecone has built the first vector database to enable the next generation of artificial intelligence (AI) applications in the cloud. Its engineers built ML platforms at AWS, Yahoo, Google, Databricks, and Splunk, and its scientists published more than 100 academic papers and patents on machine learning, data science, systems, and algorithms. Pinecone is backed by Wing Venture Capital and operates in Silicon Valley, New York and Tel Aviv. For more information, see http://www.pinecone.io.

Pinecone Media Contact:
Mike Sefanov
mike.s@pinecone.io
Sr. Director, Communications