Top Sites>The vector database to build knowledgeable AI | Pinecone

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# Host
Host: https://www.pinecone.io

# Sitemaps
Sitemap: https://www.pinecone.io/sitemap.xml

# Pinecone
> Search through billions of items for similar matches to any object, in milliseconds. It’s the next generation of search, an API call away.

[Start Building](https://www.pinecone.io/agents/pinecone/)

## About Pinecone

Pinecone is the leading vector database for building accurate and performant AI applications at scale in production. Pinecone's mission is to make AI knowledgeable. More than 9,000 customers across industries have shipped agents, search, and recommendation systems faster and more confidently with Pinecone. The company is based in New York and backed by Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital.

## Why Pinecone

We provide the vector database for developers to build the most accurate and performant AI applications at scale – and achieve the fastest time to value for their organizations.

- Provides all the components and capabilities for high-quality, accurate end-to-end retrieval in a single place:
   - Combines cutting edge models (embedding, planning, reranking) with flexible and powerful query mechanisms (vector, keywords, filtering, namespaces,...) to retrieve relevant insights from any kind of data
   - Tightly integrating leading research with engineering enables us to rapidly develop differentiated search and retrieval quality features (e.g., Pinecone's sparse embedding and reranking models)

- Core technological differentiation from the market enables industry-leading performance for large-scale retrieval
   - Proprietary record-breaking Rust implementations of algorithms based on cutting-edge research provide low latency on top of massive datasets
   - Cloud-native architecture that separates storage from compute and reads from writes allows for hands-free scaling up to millions of namespaces, billions of vectors, and 1000s of queries per second (QPS)
   - Built-in freshness means updates are indexed and searchable in seconds for highly-dynamic workloads

- Fully-managed serverless experience provides a simple journey to production for mission-critical workloads
   - No capacity planning, infrastructure management, or tuning needed
   - Enterprise features and deployment options to meet advanced compliance and security requirements
   - Highly reliable with production-grade SLAs

- Best-in-class developer experience makes Pinecone a leading choice among developers
   - Intuitive and easy-to-use APIs, SDKs, documentation, and tooling makes onboarding fast and easy
   - Expansive integrations across the ecosystem enable developers to seamlessly integrate Pinecone into their existing workflows

- Purpose-built architecture enables extremely cost-effective retrieval at scale
   - Object storage-based architecture intelligently tiers and caches data on-demand for cost-effective serving
   - Multi-tenant architecture with efficient resource packing enables customers to only pay for the exact operations they perform
   - Namespaces, delete/fetch by metadata, provisioned capacity, schemas, TTL, and other similar features simplify data and cost management in Pinecone.

## Products

- [Pinecone Vector Database](https://www.pinecone.io/product/md/)
- [Pinecone Assistant](https://www.pinecone.io/product/assistant/md/)
- [Pinecone Dedicated Read Nodes](https://www.pinecone.io/product/dedicated-read-nodes/md/)
- [Pinecone BYOC](https://www.pinecone.io/product/bring-your-own-cloud/md/)

## Navigation

- [Docs](https://docs.pinecone.io)
- [Customers](https://www.pinecone.io/customers/)
- [How Pinecone Works](https://www.pinecone.io/how-pinecone-works/md/)
- [Learn](https://www.pinecone.io/learn/)
- [Blog](https://www.pinecone.io/blog/)
- [Research](https://www.pinecone.io/research/)
- [Community](https://www.pinecone.io/community/)
- [Pricing](https://www.pinecone.io/pricing/)
- [Contact](https://www.pinecone.io/contact/)

## Learn

- [Skills and MCP and CLI, oh my!](https://www.pinecone.io/learn/skills-mcp-cli-plugins-oh-my/md/) (2026-04-22)
- [Multi-domain RAG in n8n: why one knowledge base is not enough](https://www.pinecone.io/learn/n8n-multi-domain-rag-knowledge-base/md/) (2026-03-27)
- [Building RAG workflows in n8n: choosing the right Pinecone node](https://www.pinecone.io/learn/pinecone-assistant-vs-pinecone-vector-store-node-n8n/md/) (2026-03-10)
- [RAG with Access Control](https://www.pinecone.io/learn/rag-access-control/md/) (2026-01-08)
- [Inside Pinecone: Slab Architecture](https://www.pinecone.io/learn/slab-architecture/md/) (2025-11-04)
- [What is Context Engineering?](https://www.pinecone.io/learn/context-engineering/md/) (2025-07-15)
- [Chunking Strategies for LLM Applications](https://www.pinecone.io/learn/chunking-strategies/md/) (2025-06-28)
- [Beyond the hype: Why RAG remains essential for modern AI](https://www.pinecone.io/learn/rag-2025/md/) (2025-06-25)
- [Retrieval-Augmented Generation (RAG)](https://www.pinecone.io/learn/retrieval-augmented-generation/md/) (2025-06-12)
- [Using Pinecone asynchronously with FastAPI](https://www.pinecone.io/learn/pinecone-async-fastapi/md/) (2025-05-01)
- [Don’t be dense: Launching sparse indexes in Pinecone](https://www.pinecone.io/learn/sparse-retrieval/md/) (2025-03-05)
- [Unlock High-Precision Keyword Search with pinecone-sparse-english-v0](https://www.pinecone.io/learn/learn-pinecone-sparse/md/) (2025-03-05)
- [Pinpoint references faster with citation highlights in Pinecone Assistant](https://www.pinecone.io/learn/pinecone-assistant-citation-highlights/md/) (2025-02-24)
- [Getting started with llama-text-embed-v2](https://www.pinecone.io/learn/nvidia-for-pinecone-inference/md/) (2025-02-19)
- [ How to build an agentic, chat or RAG knowledge system using Pinecone Assistant](https://www.pinecone.io/learn/pinecone-assistant/md/) (2025-01-22)
- [Building a reliable, curated, and accurate RAG system with Cleanlab and Pinecone](https://www.pinecone.io/learn/building-reliable-curated-accurate-rag/md/) (2024-10-25)
- [Four features of the Assistant API you aren't using - but should](https://www.pinecone.io/learn/assistant-api-deep-dive/md/) (2024-10-15)
- [Vectors and Graphs: Better Together](https://www.pinecone.io/learn/vectors-and-graphs-better-together/md/) (2024-09-06)
- [Llama 3.1 Agent using LangGraph and Ollama](https://www.pinecone.io/learn/langgraph-ollama-llama/md/) (2024-09-02)
- [Accelerating Legal Discovery and Analysis with Pinecone and Voyage AI](https://www.pinecone.io/learn/legal-semantic-search/md/) (2024-08-21)
- [Refine Retrieval Quality with Pinecone Rerank](https://www.pinecone.io/learn/refine-with-rerank/md/) (2024-08-15)
- [LangGraph and Research Agents](https://www.pinecone.io/learn/langgraph-research-agent/md/) (2024-07-11)
- [Build Privacy-aware AI software using Pinecone](https://www.pinecone.io/learn/privacy-aware-software/md/) (2024-07-03)
- [The Practitioner's Guide To E5](https://www.pinecone.io/learn/the-practitioners-guide-to-e5/md/) (2024-06-24)
- [Interactive Introduction to Tokenization](https://www.pinecone.io/learn/tokenization/md/) (2024-05-17)
- [A Developer’s Guide to Approximate Nearest Neighbor (ANN) Algorithms](https://www.pinecone.io/learn/a-developers-guide-to-ann-algorithms/md/) (2024-05-15)
- [Your Guide to Vectorizing Structured Text](https://www.pinecone.io/learn/structured-data/md/) (2024-03-26)
- [Advanced RAG Techniques](https://www.pinecone.io/learn/advanced-rag-techniques/md/) (2024-03-21)
- [Manage Serverless Costs with Read Units](https://www.pinecone.io/learn/read-units/md/) (2024-02-01)
- [OpenAI's Text Embeddings v3](https://www.pinecone.io/learn/openai-embeddings-v3/md/) (2024-01-25)
- [Test Pinecone Serverless at Scale with the AWS Reference Architecture](https://www.pinecone.io/learn/scaling-pinecone-serverless/md/) (2024-01-23)
- [Build a Wikipedia chatbot, minus hallucinations ](https://www.pinecone.io/learn/wikipedia-chatbot/md/) (2024-01-15)
- [Getting Started with Mixtral 8X7B](https://www.pinecone.io/learn/mixtral-8x7b/md/) (2023-12-20)
- [Exploring the Pinecone AWS Reference Architecture](https://www.pinecone.io/learn/aws-reference-architecture/md/) (2023-11-27)
- [OpenAI Assistants API vs Canopy: A Quick Comparison](https://www.pinecone.io/learn/assistants-api-canopy/md/) (2023-11-09)
- [Making it easier to maintain open-source projects with CodiumAI and Pinecone](https://www.pinecone.io/learn/codiumai-pinecone-similar-issues/md/) (2023-09-27)
- [Making Retrieval Augmented Generation Fast](https://www.pinecone.io/learn/fast-retrieval-augmented-generation/md/) (2023-09-13)
- [An (Opinionated) Checklist to Choose a Vector Database](https://www.pinecone.io/learn/an-opinionated-checklist-to-choose-a-vector-database/md/) (2023-09-13)
- [Falcon 180B: Model Overview](https://www.pinecone.io/learn/falcon-180b/md/) (2023-09-07)
- [LLMs Are Not All You Need](https://www.pinecone.io/learn/llm-ecosystem/md/) (2023-09-06)
- [Fine-Tuning OpenAI's GPT 3.5 Turbo](https://www.pinecone.io/learn/fine-tune-gpt-3.5/md/) (2023-08-28)
- [Deploying Open Source LLMs for RAG with SageMaker](https://www.pinecone.io/learn/sagemaker-rag/md/) (2023-08-23)
- [How to use Jupyter Notebooks for Machine Learning and AI Tasks](https://www.pinecone.io/learn/jupyter-notebooks/md/) (2023-08-23)
- [Options for Solving Hallucinations in Generative AI](https://www.pinecone.io/learn/options-for-solving-hallucinations-in-generative-ai/md/) (2023-08-21)
- [AI-powered and built with... JavaScript?](https://www.pinecone.io/learn/javascript-ai/md/) (2023-08-11)
- [NeMo Guardrails: The Missing Manual](https://www.pinecone.io/learn/nemo-guardrails-intro/md/) (2023-08-11)
- [Image Search in Typescript](https://www.pinecone.io/learn/image-search-in-typescript/md/) (2023-08-08)
- [Llama 2: AI Developers Handbook](https://www.pinecone.io/learn/llama-2/md/) (2023-07-24)
- [Retrieval Augmented Generation (RAG) with Pinecone and Vercel's AI SDK](https://www.pinecone.io/learn/context-aware-chatbot-with-vercel-ai-sdk/md/) (2023-07-19)
- [Understanding Hallucinations in AI: A Comprehensive Guide](https://www.pinecone.io/learn/ai-hallucinations/md/) (2023-07-13)
- [Audio Recommendation with OpenAI and Vector DBs](https://www.pinecone.io/learn/audio-recommendation-openai/md/) (2023-07-10)
- [Semantic search with Pinecone](https://www.pinecone.io/learn/search-with-pinecone/md/) (2023-06-30)
- [Embeddings to Identify Fake News](https://www.pinecone.io/learn/embeddings-identify-fake-news/md/) (2023-06-30)
- [Evaluation Measures in Information Retrieval](https://www.pinecone.io/learn/offline-evaluation/md/) (2023-06-30)
- [Softmax Activation Function: Everything You Need to Know](https://www.pinecone.io/learn/softmax-activation/md/) (2023-06-30)
- [Generative Question-Answering with Long-Term Memory](https://www.pinecone.io/learn/openai-gen-qa/md/) (2023-06-30)
- [What are Vector Embeddings](https://www.pinecone.io/learn/vector-embeddings/md/) (2023-06-30)
- [Getting Started with Hybrid Search](https://www.pinecone.io/learn/hybrid-search-intro/md/) (2023-06-30)
- [Cross-Entropy Loss: Make Predictions with Confidence](https://www.pinecone.io/learn/cross-entropy-loss/md/) (2023-06-30)
- [K-Nearest Neighbor (KNN) Explained](https://www.pinecone.io/learn/k-nearest-neighbor/md/) (2023-06-30)
- [Optimize Classifier Training with Vector Search](https://www.pinecone.io/learn/classifier-train-vector-search/md/) (2023-06-30)
- [How Language Embedding Models Will Change Financial Services](https://www.pinecone.io/learn/nlp-financial-services/md/) (2023-06-30)
- [Long Form Question Answering in Haystack](https://www.pinecone.io/learn/haystack-lfqa/md/) (2023-06-30)
- [Using Semantic Search to Find GIFs](https://www.pinecone.io/learn/gif-search/md/) (2023-06-30)
- [Time Series Analysis Through Vectorization](https://www.pinecone.io/learn/time-series-vectors/md/) (2023-06-30)
- [Introduction to K-Means Clustering](https://www.pinecone.io/learn/k-means-clustering/md/) (2023-06-30)
- [The Missing WHERE Clause in Vector Search](https://www.pinecone.io/learn/vector-search-filtering/md/) (2023-06-30)
- [Text-to-Image and Image-to-Image Search Using CLIP](https://www.pinecone.io/learn/clip-image-search/md/) (2023-06-30)
- [Hybrid Search and Learning-to-Rank with Metarank](https://www.pinecone.io/learn/metarank/md/) (2023-06-30)
- [Introduction to Transfer Learning](https://www.pinecone.io/learn/transfer-learning/md/) (2023-06-30)
- [Fixing YouTube Search with OpenAI's Whisper](https://www.pinecone.io/learn/openai-whisper/md/) (2023-06-30)
- [Vector Embeddings for Developers: The Basics](https://www.pinecone.io/learn/vector-embeddings-for-developers/md/) (2023-06-30)
- [Building a Image Recognition App in Javascript using Pinecone, Hugging Face, and Vercel](https://www.pinecone.io/learn/pinecone-vision-app/md/) (2023-06-30)
- [Transformers Are All You Need](https://www.pinecone.io/learn/transformers/md/) (2023-06-30)
- [Semantic Search: Measuring Meaning From Jaccard to Bert](https://www.pinecone.io/learn/semantic-search/md/) (2023-06-30)
- [Weight Initialization Techniques in Neural Networks](https://www.pinecone.io/learn/weight-initialization/md/) (2023-06-30)
- [How Machine Learning is Accelerating Life Sciences](https://www.pinecone.io/learn/ml-life-sciences/md/) (2023-06-30)
- [What is Similarity Search?](https://www.pinecone.io/learn/what-is-similarity-search/md/) (2023-06-30)
- [Regularization in Neural Networks](https://www.pinecone.io/learn/regularization-in-neural-networks/md/) (2023-06-30)
- [Making Stable Diffusion Faster with Intelligent Caching](https://www.pinecone.io/learn/faster-stable-diffusion/md/) (2023-06-30)
- [Streaming Embedding Generation with Databricks and Pinecone](https://www.pinecone.io/learn/databricks-streaming/md/) (2023-06-30)
- [Building a Multi-User Chatbot with Langchain and Pinecone in Next.JS](https://www.pinecone.io/learn/javascript-chatbot/md/) (2023-06-30)
- [Plagiarism Detection Using Transformers](https://www.pinecone.io/learn/plagiarism-detection/md/) (2023-06-30)
- [Making YouTube Search Better with NLP](https://www.pinecone.io/learn/youtube-search/md/) (2023-06-30)
- [Ludicrous BERT Search Speeds](https://www.pinecone.io/learn/bert-search-speed/md/) (2023-06-30)
- [Vector Similarity Explained](https://www.pinecone.io/learn/vector-similarity/md/) (2023-06-30)
- [Testing p2 Pods, Vertical Scaling, and Collections](https://www.pinecone.io/learn/testing-p2-collections-scaling/md/) (2023-06-30)
- [How to Explain ConvNet Predictions Using Class Activation Maps](https://www.pinecone.io/learn/class-activation-maps/md/) (2023-06-30)
- [SPLADE for Sparse Vector Search Explained](https://www.pinecone.io/learn/splade/md/) (2023-06-30)
- [Straightforward Guide to Dimensionality Reduction](https://www.pinecone.io/learn/dimensionality-reduction/md/) (2023-06-30)
- [Chatbots with Pinecone](https://www.pinecone.io/learn/chatbots-with-pinecone/md/) (2023-06-23)
- [Build Better Deep Learning Models with Batch and Layer Normalization](https://www.pinecone.io/learn/batch-layer-normalization/md/) (2023-06-23)
- [Advanced Topic Modeling with BERTopic](https://www.pinecone.io/learn/bertopic/md/) (2023-06-23)
- [What is Vector Search? 2024 Guide for Developers](https://www.pinecone.io/learn/vector-search-basics/md/) (2023-06-22)
- [What is a Vector Database & How Does it Work? Use Cases + Examples](https://www.pinecone.io/learn/vector-database/md/) (2023-05-03)

## Series

### Beyond Retrieval
- [Knowledge needs a meta-knowledge layer](https://www.pinecone.io/learn/series/beyond-retrieval/knowledge-needs-meta-knowledge/md/) (2026-03-09)
- [True, Relevant, and Wrong: The Applicability Problem in RAG](https://www.pinecone.io/learn/series/beyond-retrieval/rag-applicability-problem/md/) (2026-02-12)

### Unlock Real-time Data for AI with Estuary Flow and Pinecone
- [Real-time RAG with Pinecone and Estuary Flow](https://www.pinecone.io/learn/series/unlock-real-time-data-for-ai-with-estuary-flow-and-pinecone/real-time-rag-pinecone-estuary-flow/md/) (2024-12-18)
- [BigQuery to Pinecone in Real-Time with Estuary Flow](https://www.pinecone.io/learn/series/unlock-real-time-data-for-ai-with-estuary-flow-and-pinecone/bigquery-pinecone-real-time-estuary-flow/md/) (2024-12-18)

### Vector Databases in Production for Busy Engineers
- [Deploying Pinecone with Infrastructure as Code (IaC)](https://www.pinecone.io/learn/series/vector-databases-in-production-for-busy-engineers/pinecone-iac/md/) (2024-10-02)
- [Streamlining CI/CD with Pinecone Local](https://www.pinecone.io/learn/series/vector-databases-in-production-for-busy-engineers/cicd-pinecone-local/md/) (2024-10-02)
- [Designing a RAG Pipeline (Interactive)](https://www.pinecone.io/learn/series/vector-databases-in-production-for-busy-engineers/rag-pipeline-design/md/) (2024-06-06)
- [RAG Evaluation: Don’t let customers tell you first](https://www.pinecone.io/learn/series/vector-databases-in-production-for-busy-engineers/rag-evaluation/md/) (2024-05-07)
- [Integrating cloud-based vector databases with CI/CD Pipelines](https://www.pinecone.io/learn/series/vector-databases-in-production-for-busy-engineers/ci-cd/md/) (2024-05-03)
- [Multi-Tenancy in Vector Databases](https://www.pinecone.io/learn/series/vector-databases-in-production-for-busy-engineers/vector-database-multi-tenancy/md/) (2024-04-18)

### Scaling AI Applications with Pinecone and Kubernetes
- [Scaling AI Applications with Pinecone and Kubernetes - Ingestion Microservices](https://www.pinecone.io/learn/series/kubernetes/scaling-ai-apps-ingestion/md/) (2024-02-07)
- [Scaling AI Applications with Kubernetes and Pinecone - Introduction](https://www.pinecone.io/learn/series/kubernetes/scaling-ai-apps-kubernetes-and-pinecone-intro/md/) (2023-12-08)

### Retrieval Augmented Generation
- [Metrics-Driven Agent Development](https://www.pinecone.io/learn/series/rag/ragas/md/) (2024-02-23)
- [Choosing an Embedding Model](https://www.pinecone.io/learn/series/rag/embedding-models-rundown/md/) (2024-01-17)
- [Rerankers and Two-Stage Retrieval](https://www.pinecone.io/learn/series/rag/rerankers/md/) (2023-10-27)

### Data Sync and Search: Pinecone and Airbyte
- [Postgres to Pinecone Syncing](https://www.pinecone.io/learn/series/airbyte/airbyte-postgres-to-pinecone/md/) (2023-10-11)
- [Introduction to Airbyte and the Pinecone connector](https://www.pinecone.io/learn/series/airbyte/airbyte-and-pinecone-intro/md/) (2023-08-29)

### LangChain AI Handbook
- [LangChain Expression Language Explained](https://www.pinecone.io/learn/series/langchain/langchain-expression-language/md/) (2023-12-04)
- [Building Custom Tools for LLM Agents](https://www.pinecone.io/learn/series/langchain/langchain-tools/md/) (2023-06-30)
- [Superpower LLMs with Conversational Agents](https://www.pinecone.io/learn/series/langchain/langchain-agents/md/) (2023-06-30)
- [Fixing Hallucination with Knowledge Bases](https://www.pinecone.io/learn/series/langchain/langchain-retrieval-augmentation/md/) (2023-06-30)
- [Conversational Memory for LLMs with Langchain](https://www.pinecone.io/learn/series/langchain/langchain-conversational-memory/md/) (2023-06-30)
- [Prompt Engineering and LLMs with Langchain](https://www.pinecone.io/learn/series/langchain/langchain-prompt-templates/md/) (2023-06-30)
- [LangChain: Introduction and Getting Started](https://www.pinecone.io/learn/series/langchain/langchain-intro/md/) (2023-06-30)

### Embedding Methods for Image Search
- [Zero Shot Object Detection with OpenAI's CLIP](https://www.pinecone.io/learn/series/image-search/zero-shot-object-detection-clip/md/) (2023-06-30)
- [Zero-shot Image Classification with OpenAI's CLIP](https://www.pinecone.io/learn/series/image-search/zero-shot-image-classification-clip/md/) (2023-06-30)
- [Multi-modal ML with OpenAI's CLIP](https://www.pinecone.io/learn/series/image-search/clip/md/) (2023-06-30)
- [Vision Transformers (ViT) Explained](https://www.pinecone.io/learn/series/image-search/vision-transformers/md/) (2023-06-30)
- [Visual Guide to Applied Convolution Neural Networks](https://www.pinecone.io/learn/series/image-search/cnn/md/) (2023-06-30)
- [AlexNet and ImageNet: The Birth of Deep Learning](https://www.pinecone.io/learn/series/image-search/imagenet/md/) (2023-06-30)
- [Bag of Visual Words](https://www.pinecone.io/learn/series/image-search/bag-of-visual-words/md/) (2023-06-30)
- [Color Histograms in Image Retrieval](https://www.pinecone.io/learn/series/image-search/color-histograms/md/) (2023-06-30)

### Faiss: The Missing Manual
- [Facebook AI and the Index Factory](https://www.pinecone.io/learn/series/faiss/composite-indexes/md/) (2023-06-30)
- [Hierarchical Navigable Small Worlds (HNSW)](https://www.pinecone.io/learn/series/faiss/hnsw/md/) (2023-06-30)
- [Product Quantization: Compressing high-dimensional vectors by 97%](https://www.pinecone.io/learn/series/faiss/product-quantization/md/) (2023-06-30)
- [Random Projection for Locality Sensitive Hashing](https://www.pinecone.io/learn/series/faiss/locality-sensitive-hashing-random-projection/md/) (2023-06-30)
- [Locality Sensitive Hashing (LSH): The Illustrated Guide](https://www.pinecone.io/learn/series/faiss/locality-sensitive-hashing/md/) (2023-06-30)
- [Nearest Neighbor Indexes for Similarity Search](https://www.pinecone.io/learn/series/faiss/vector-indexes/md/) (2023-06-30)
- [Introduction to Facebook AI Similarity Search (Faiss)](https://www.pinecone.io/learn/series/faiss/faiss-tutorial/md/) (2023-06-30)

### Vector Search in the Wild
- [How Nyckel Built An API for Semantic Image Search](https://www.pinecone.io/learn/series/wild/nyckel-ml-automation/md/) (2023-06-30)
- [Detecting Similar Security Alerts at Expel](https://www.pinecone.io/learn/series/wild/expel-alert-similarity/md/) (2023-06-30)
- [Building the Self-Organizing Workspace at Mem](https://www.pinecone.io/learn/series/wild/mem-semantic-search/md/) (2023-06-30)
- [How Spotify Uses Semantic Search for Podcasts](https://www.pinecone.io/learn/series/wild/spotify-podcast-search/md/) (2023-06-30)

### Natural Language Processing for Semantic Search
- [Domain Adaptation with Generative Pseudo-Labeling (GPL)](https://www.pinecone.io/learn/series/nlp/gpl/md/) (2023-06-30)
- [Unsupervised Training of Retrievers Using GenQ](https://www.pinecone.io/learn/series/nlp/genq/md/) (2023-06-30)
- [Making the Most of Data: Domain Transfer with BERT](https://www.pinecone.io/learn/series/nlp/domain-transfer/md/) (2023-06-30)
- [Making the Most of Data: Augmentation with BERT](https://www.pinecone.io/learn/series/nlp/data-augmentation/md/) (2023-06-30)
- [Reader Models for Open Domain Question-Answering](https://www.pinecone.io/learn/series/nlp/reader-models/md/) (2023-06-30)
- [Retriever Models for Open Domain Question-Answering](https://www.pinecone.io/learn/series/nlp/retriever-models/md/) (2023-06-30)
- [An Introduction to Open Domain Question-Answering](https://www.pinecone.io/learn/series/nlp/question-answering/md/) (2023-06-30)
- [Unsupervised Training for Sentence Transformers](https://www.pinecone.io/learn/series/nlp/unsupervised-training-sentence-transformers/md/) (2023-06-30)
- [Tomayto, Tomahto, Transformer: Multilingual Sentence Transformers](https://www.pinecone.io/learn/series/nlp/multilingual-transformers/md/) (2023-06-30)
- [Next-Gen Sentence Embeddings with Multiple Negatives Ranking Loss](https://www.pinecone.io/learn/series/nlp/fine-tune-sentence-transformers-mnr/md/) (2023-06-30)
- [Training Sentence Transformers the OG Way (with Softmax Loss)](https://www.pinecone.io/learn/series/nlp/train-sentence-transformers-softmax/md/) (2023-06-28)
- [Sentence Transformers: Meanings in Disguise](https://www.pinecone.io/learn/series/nlp/sentence-embeddings/md/) (2023-06-28)
- [Dense Vectors: Capturing Meaning with Code](https://www.pinecone.io/learn/series/nlp/dense-vector-embeddings-nlp/md/) (2023-06-28)


## Blog

- [Four New GA Features for Dedicated Read Nodes That Give Teams More Control and Observability](https://www.pinecone.io/blog/dedicated-read-nodes-ga-features/md/) (2026-04-15)
- [Pinecone Dedicated Read Nodes: Now Generally Available](https://www.pinecone.io/blog/dedicated-read-nodes-ga/md/) (2026-04-15)
- [Load Balancing AI Services for Availability and Speed](https://www.pinecone.io/blog/load-balancing/md/) (2026-04-14)
- [Pinecone Assistant: A Managed Knowledge Layer for Production AI Applications](https://www.pinecone.io/blog/assistant-managed-knowledge-layer/md/) (2026-04-02)
- [Garbage Day: How Pinecone Safely Deletes Billions of Objects at Scale](https://www.pinecone.io/blog/janitor/md/) (2026-03-05)
- [When "Performance" Means Two Different Things](https://www.pinecone.io/blog/performance-as-a-measurement/md/) (2026-03-03)
- [Pinecone BYOC: Pinecone in your AWS, GCP, or Azure account, no vendor access](https://www.pinecone.io/blog/byoc/md/) (2026-02-19)
- [Use the Pinecone Plugin for Claude Code to develop AI Applications Faster](https://www.pinecone.io/blog/pinecone-plugin-for-claude-code/md/) (2026-02-11)
- [Millions at Stake: How Melange's High-Recall Retrieval Prevents Litigation Collapse](https://www.pinecone.io/blog/millions-at-stake-melange/md/) (2026-02-09)
- [Pinecone Assistant Node in n8n: Turn Any Data Source Into Knowledge](https://www.pinecone.io/blog/pinecone-assistant-node/md/) (2026-01-28)
- [Pinecone Dedicated Read Nodes are now in Public Preview](https://www.pinecone.io/blog/dedicated-read-nodes/md/) (2025-12-01)
- [New Bulk Data Operations: Update, Delete, and Fetch by Metadata](https://www.pinecone.io/blog/update-delete-and-fetch-by-metadata/md/) (2025-10-30)

## Case Studies

- [ZoomInfo delivers high-quality, real-time contact recommendations for GTM teams with Pinecone, driving a 50% increase in user engagement](https://www.pinecone.io/customers/zoominfo/md/) (2026-04-15)
- [Allspice Transforms the Culinary Experience with Semantic Search Powered by Pinecone](https://www.pinecone.io/customers/allspice/md/) (2026-03-25)
- [Powering high-stakes patent search at scale: How Melange built a reliable AI system on Pinecone](https://www.pinecone.io/customers/melange/md/) (2026-02-09)
- [Fast, accurate retrieval for creators at scale: Delphi’s path toward a million conversational agents with Pinecone](https://www.pinecone.io/customers/delphi/md/) (2025-08-21)
- [Obviant makes 30% more accurate defense acquisition recommendations combining sparse and dense retrieval with Pinecone](https://www.pinecone.io/customers/obviant/md/) (2025-06-24)
- [Terminal X AI agents, powered by Pinecone, turn complex financial data into production-grade insights at scale](https://www.pinecone.io/customers/terminal-x/md/) (2025-06-09)
- [Aquant delivers scalable, expert-level service intelligence with Pinecone](https://www.pinecone.io/customers/aquant/md/) (2025-06-04)
- [Domain-specific AI agents at scale: CustomGPT.ai serves 10,000+ customers with Pinecone](https://www.pinecone.io/customers/customgpt-ai/md/) (2025-05-06)
- [How Vanguard worked with Pinecone to boost customer support with faster calls and 12% more accurate responses](https://www.pinecone.io/customers/vanguard/md/) (2025-03-25)
- [How 1up turns sales reps into product experts with Pinecone](https://www.pinecone.io/customers/1up/md/) (2025-03-06)
- [Stravito turns market and consumer data into actionable insights with Pinecone Inference](https://www.pinecone.io/customers/stravito/md/) (2024-12-17)
- [Pinecone Helps Deep Talk Deliver World-Class AI Assistants with  Lower Engineering Overhead](https://www.pinecone.io/customers/deep-talk/md/) (2024-09-03)
- [Assembled Delivers Better, Faster AI- Driven Support with Pinecone](https://www.pinecone.io/customers/assembled/md/) (2024-09-03)
- [TaskUs Partners with Pinecone to Enhance Customer Service Satisfaction](https://www.pinecone.io/customers/taskus/md/) (2024-05-10)
- [InpharmD Redefines Evidence-Based Healthcare with Pinecone](https://www.pinecone.io/customers/inpharmd/md/) (2024-03-11)
- [DISCO Revolutionizes Legal Technology with Pinecone](https://www.pinecone.io/customers/disco/md/) (2024-01-22)
- [Revolutionizing Revenue Intelligence: Gong's Strategic Partnership with Pinecone](https://www.pinecone.io/customers/gong/md/) (2024-01-16)
- [Chipper Cash thwarts fraudsters in real-time with Pinecone](https://www.pinecone.io/customers/chipper-cash/md/) (2023-04-12)

## Research Publications

- [Accurate and Efficient Metadata Filtering in Pinecone’s Serverless Vector Database](https://www.pinecone.io/research/accurate-and-efficient-metadata-filtering-in-pinecones-serverless-vector-database/md/) (2025-06-12)
- [Unveiling DIME: Reproducibility, Scalability, and Formal Analysis of Dimension Importance Estimation for Dense Retrieval](https://www.pinecone.io/research/unveiling-dime-reproducibility-scalability-and-formal-analysis-of-dimension-importance-estimation-for-dense-retrieval/md/) (2025-05-09)
- [Fast and Effective Early Termination for Simple Ranking Functions](https://www.pinecone.io/research/fast-and-effective-early-termination-for-simple-ranking-functions/md/) (2025-05-07)
- [A Flexible Resource for Top-Weighted Comparisons Between Sets and Rankings](https://www.pinecone.io/research/a-flexible-resource-for-top-weighted-comparisons-between-sets-and-rankings/md/) (2025-05-01)
- [E2Rank: Efficient and Effective Layer-wise Reranking](https://www.pinecone.io/research/e2rank-efficient-and-effective-layer-wise-reranking/md/) (2025-04-10)
- [ColBERT-serve: Efficient Multi-Stage Memory-Mapped Scoring](https://www.pinecone.io/research/colbert-serve-efficient-multi-stage-memory-mapped-scoring/md/) (2025-04-07)
- [Efficient Constant-Space Multi-Vector Retrieval](https://www.pinecone.io/research/efficient-constant-space-multi-vector-retrieval/md/) (2025-04-07)
- [Natural Language Counterfactual Explanations for Graphs Using Large Language Models](https://www.pinecone.io/research/natural-language-counterfactual-explanations-for-graphs-using-large-language-models/md/) (2025-01-27)
- [Results of the Big ANN: NeurIPS'23 competition](https://www.pinecone.io/research/results-of-the-big-ann-neurips-23-competition/md/) (2024-09-25)
- [Bridging Dense and Sparse Maximum Inner Product Search](https://www.pinecone.io/research/bridging-dense-and-sparse-maximum-inner-product-search/md/) (2024-08-19)
- [Foundations of Vector Retrieval](https://www.pinecone.io/research/foundations-of-vector-retrieval/md/) (2024-06-15)
- [Rank-Biased Quality Measurement for Sets and Rankings](https://www.pinecone.io/research/rank-biased-quality-measurement-for-sets-and-rankings/md/) (2024-06-01)
- [DeeperImpact: Optimizing Sparse Learned Index Structures](https://www.pinecone.io/research/deeperimpact-optimizing-sparse-learned-index-structures/md/) (2024-05-27)
- [Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search](https://www.pinecone.io/research/optimistic-query-routing-in-clustering-based-approximate-maximum-inner-product-search/md/) (2024-05-20)
- [Faster Learned Sparse Retrieval with Block-Max Pruning](https://www.pinecone.io/research/faster-learned-sparse-retrieval-with-block-max-pruning/md/) (2024-05-02)
- [Improved Learned Sparse Retrieval with Corpus-specific Vocabularies](https://www.pinecone.io/research/improved-learned-sparse-retrieval-with-corpus-specific-vocabularies/md/) (2024-03-23)
- [Efficient and Effective Tree-based and Neural Learning to Rank](https://www.pinecone.io/research/efficient-and-effective-tree-based-and-neural-learning-to-rank/md/) (2023-12-01)
- [Enhancing Sparse Retrieval via Unsupervised Learning](https://www.pinecone.io/research/enhancing-sparse-retrieval-via-unsupervised-learning/md/) (2023-11-26)
- [An Approximate Algorithm for Maximum Inner Product Search over Streaming Sparse Vectors](https://www.pinecone.io/research/an-approximate-algorithm-for-maximum-inner-product-search-over-streaming-sparse-vectors/md/) (2023-11-08)
- [An Analysis of Fusion Functions for Hybrid Retrieval](https://www.pinecone.io/research/an-analysis-of-fusion-functions-for-hybrid-retrieval/md/) (2023-08-18)
- [Yggdrasil Decision Forests: A Fast and Extensible Decision Forests Library](https://www.pinecone.io/research/yggdrasil-decision-forests-a-fast-and-extensible-decision-forests-library/md/) (2023-08-04)
- [Exact PPS Sampling w/ Bounded Sample Size](https://www.pinecone.io/research/exact-pps-sampling-w-bounded-sample-size/md/) (2023-05-01)
- [Lower Bounds for Pseudo-Deterministic Counting in a Stream](https://www.pinecone.io/research/lower-bounds-for-pseudo-deterministic-counting-in-a-stream/md/) (2023-03-23)
- [SDR: Efficient Neural Re-ranking using Succinct Document Representation](https://www.pinecone.io/research/sdr-efficient-neural-re-ranking-using-succinct-document-representation/md/) (2022-05-31)
- [Relative Error Streaming Quantiles](https://www.pinecone.io/research/relative-error-streaming-quantiles/md/) (2021-12-07)
- [Projective Clustering Product Quantization](https://www.pinecone.io/research/projective-clustering-product-quantization/md/) (2021-12-03)

## Social

- [Twitter / X](https://x.com/pinecone)
- [LinkedIn](https://www.linkedin.com/company/pinecone-io)
- [YouTube](https://www.youtube.com/@pinecone-io)
- [GitHub](https://github.com/pinecone-io)
- [Discord](https://discord.gg/qU3yVdqRda)