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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
Pinecone Makes Accurate, Fast, Scalable Generative AI Accessible to Organizations Large and Small with Launch of its Serverless Vector Database
2024-05-22 · via Pinecone

Pinecone serverless is now generally available for mission-critical workloads

More than 20,000 organizations build with Pinecone serverless in public preview

NEW YORK, May 21, 2024 /PRNewswire/ -- Pinecone, a leading vector database company, today launched Pinecone serverless into general availability. The state-of-the-art vector database designed to make generative artificial intelligence (AI) accurate, fast, and scalable is now ready for mission-critical workloads.

"Businesses are already building delightful and knowledgeable AI products with Pinecone," said Edo Liberty, founder and CEO of Pinecone. "After making these products work in the lab, developers want to launch these products to thousands or millions of users. This makes considerations like operating costs, performance at scale, high availability and support, and security matter a lot. This is where Pinecone serverless shines, and why it's the most trusted vector database for production applications."

Confidently moving forward with AI

Pinecone serverless has been battle-tested with rapid adoption over the course of four months in Public Preview mode. More than 20,000 organizations have used it to date. Large, critical workloads with billions of vectors are also running with select customers, making up part of the collective 12 billion embeddings already indexed on the new architecture. Serverless users, large and small, include organizations like Gong, Help Scout, New Relic, Notion, TaskUs, and You.com. With Pinecone serverless, these organizations are eliminating significant operational overhead by reducing costs up to 50x, and building more accurate AI applications at scale.

Making AI knowledgeable

Pinecone research shows that the most effective method to improve the quality of generative AI results and reduce hallucinations – unintended, false, or misleading information presented as fact – is by using a vector database for Retrieval-augmented Generation (RAG). A detailed study from AI consulting services firm Prolego supports the findings that RAG significantly improves the performance of large language models (LLMs). For example, compared with the well-known GPT-4 LLM alone, GPT-4 with RAG and sufficient data reduces the frequency of unhelpful answers from GPT-4 by 50% for the "faithfulness" metric, even on information that the LLM was trained on. Moreover, as more data becomes available for context retrieval, the more accurate results become.

Making AI easy and affordable with the best database architecture

Pinecone serverless is architected from the ground up to provide low-latency, always-fresh vector search over unrestricted data sizes at low cost. This is making generative AI easily accessible.

Separation of reads from writes, and storage from compute in Pinecone serverless significantly reduces costs for all types and sizes of workloads. First-of-their-kind indexing and retrieval algorithms enable fast and memory-efficient vector search from object storage without sacrificing retrieval quality.

Introducing Private Endpoints

Security, privacy, and compliance are paramount for businesses as they fuel artificial intelligence with more and more data. Today, Pinecone is unveiling Private Endpoints in public preview to help ensure customer data adheres to these demands, as well as governance and regulatory compliance.

Private Endpoints support direct and secure data plane connectivity from an organization's virtual private cloud (VPC) to their Pinecone index over AWS PrivateLink, an Amazon Web Services (AWS) offering that provides private connectivity between VPCs, supported AWS services, and on-premises networks without exposing traffic to the public Internet.

Building with the AI Stack

To make building AI applications as simple as possible, Pinecone serverless is launching with a growing number of partner integrations. Companies in Pinecone's recently-announced partner program can now let their users seamlessly connect with and use Pinecone directly inside those users' coding environments. These companies include Anyscale, AWS, Confluent, LangChain, Mistral, Monte Carlo, Nexla, Pulumi, Qwak, Together.ai, Vectorize, and Unstructured. Pinecone is also working with service integrator partners like phData to help joint customers onboard to Serverless.

Get started with Pinecone serverless for free, today.

Read the launch announcement blog and learn more about Private Endpoints for Pinecone serverless.

Customer Quotes

  • Jacob Eckel, VP, R&D Division Manager, Gong
    "Pinecone serverless isn't just a cost-cutting move for us; it is a strategic shift towards a more efficient, scalable, and resource-effective solution."
  • Luis Morales, VP of Engineering, Help Scout
    "At Help Scout, Pinecone's scalable, serverless architecture is crucial for powering AI innovation and delighting customers. It enables our engineering teams to seamlessly integrate new features, pushing the boundaries of customer support. With Pinecone, we're setting the pace in a vibrant tech landscape."
  • New Relic Chief Strategy and Design Officer Peter Pezaris
    "With New Relic AI, our generative AI assistant, engineers can use natural language to explore vast amounts of telemetry and access our all-in-one observability platform. By adding Pinecone vector databases for semantic search and RAG to our unified platform, we have enriched the data set our users can draw insights from and introduced new features that help engineers take action on data faster. Pinecone aligns with our vision to democratize data accessibility for all engineers, and we're excited to uncover more potential with its new serverless architecture."
  • Akshay Kothari, Co-Founder and COO, Notion
    "Notion is leading the AI productivity revolution. Our launch of a first-to-market AI feature was made possible by Pinecone serverless. Their technology enables our Q&A AI to deliver instant answers to millions of users, sourced from billions of documents. Best of all, our move to their latest architecture has cut our costs by 60%, advancing our mission to make software toolmaking ubiquitous."
  • Manish Pandya, SVP of Digital Transformation, TaskUs
    "Pinecone has transformed our customer service operations, enabling us to achieve unprecedented levels of efficiency and customer satisfaction. We are prioritizing its serverless architecture to support our diverse portfolio of AI products across multiple regions. With our scale and ambitions, Pinecone is an integral component of our TaskGPT platform."
  • Bryan McCann, CTO & Co-Founder, You.com
    "No other vector database matches Pinecone's scalability and production readiness. We are excited to explore how Pinecone serverless will support the growth of our product capabilities."

About Pinecone

Pinecone created the vector database to help engineers build and scale remarkable AI applications. Vector databases have become a core component of GenAI applications, and Pinecone is the market-leading solution with over 5,000 customers of all types and sizes across all industries. Pinecone has raised $138M in funding from leading investors Andreessen Horowitz, ICONIQ Growth, Menlo Ventures, and Wing Venture Capital, and operates in New York, San Francisco, and Tel Aviv.