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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
Pinecone Recognized as a 2021 Gartner® Cool Vendor in Art...
2021-10-29 · via Pinecone

SAN FRANCISCO, Oct. 28, 2021 /PRNewswire/ -- Pinecone Systems Inc., a machine learning (ML) cloud infrastructure company, announced today that it has been named a Gartner Cool Vendor in the October 2021 Gartner Cool Vendors™ in Data for Artificial Intelligence and Machine Learning*.

According to the report, "As AI and ML techniques become common in the enterprise, data is coming to the foreground. Data is what makes a difference in AI now. Data and analytics leaders want to improve the delivery of AI results with data innovations." The report also noted that "AI teams are expanding their focus from model development to data that makes these models effective. Many of them are unaware of the proven data management solutions and are looking for AI-specific data offerings to improve and simplify their data-related efforts."

Vector search can be more accurate and intuitive than traditional keyword search methods, which require the user to make guesses about how data is structured. Before Pinecone, only a few tech giants had the engineering resources and budgets to build their own vector databases. Pinecone's fully-managed vector database enables organizations of any size to quickly move similarity search and recommendation engines into production without tasking a large group of ML and database engineers to build and maintain one of their own.

Vector databases often require expensive infrastructures to operate and are notoriously difficult to manage. Pinecone solves both of these challenges with a solution that was built to efficiently store and query vector data within a platform that is easy to use.

"We are honored to be recognized as a 2021 Gartner Cool Vendor which we believe is a powerful recognition of the value of vector databases and our work to expand AI-based search technology," said Edo Liberty, Founder & CEO of Pinecone. "We introduced the vector database and we continue to work with our customers to ensure it powers the best search and recommendation experiences available."

Gartner clients can access the full report.

*Gartner, "Cool Vendors in Data for Artificial Intelligence and Machine Learning," Svetlana Sicular, Chirag Dekate, Anthony Mullen, Arun Chandrasekaran, Afraz Jaffri, October 13, 2021

Gartner Disclaimer:

GARTNER and COOL VENDORS are registered trademarks and service marks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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 (Amazon SageMaker), 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.

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