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 5000 customers across various industries have shipped AI applications faster and more confidently with Pinecone's developer-friendly technology. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. For more information, visit pinecone.io.

Agent Infrastructure

Visit Website

Founded

2019

Location

New York, NY

Employees

133

Funding

$138M Series B

Pinecone — Serverless Vector Database for Production AI

[Visit Pinecone](https://www.pinecone.io) | Explore the [documentation](https://docs.pinecone.io)

Overview

**Pinecone** is a serverless vector database purpose‑built for production AI workloads. It powers fast, accurate retrieval for **RAG (retrieval‑augmented generation)**, **semantic search**, **recommendations**, and **agent memory**—scaling reliably from prototypes to billions of vectors with low latency and simplified operations.

**Core value:** reliable vector search, simplified ops, and rapid time‑to‑value for data and ML teams shipping AI in production.

**Who it’s for:** product search teams, knowledge assistant builders, support copilots, and agentic systems operating across millions of small namespaces.

**Where it runs:** cloud‑native with popular integrations across [AWS](https://aws.amazon.com), [Google Cloud](https://cloud.google.com), and [Microsoft Azure](https://azure.microsoft.com).

Product Highlights

**Serverless scalability:** elastically scale to billions of vectors without managing clusters.

**Hybrid dense + sparse search:** combine embeddings with sparse signals (e.g., BM25) for highly relevant results.

**Low‑latency retrieval:** optimized for high‑throughput, real‑time applications.

**Strong metadata filtering:** precise filtering for multi‑faceted search and policy‑aware retrieval.

**Multi‑tenant namespaces:** isolate data per customer, team, or application at scale.

**On‑demand caching:** speed up hot queries and reduce compute costs.

**Enterprise‑ready:** SOC 2, ISO 27001, GDPR, and HIPAA support.

Pinecone Assistant (API)

Ship chat and agent applications faster with an API that handles the heavy lifting:

**Automated pipeline:** ingestion, chunking, embeddings, retrieval, and streaming responses.

**Glue‑code reduction:** eliminate boilerplate and orchestrate RAG with minimal custom code.

**Ideal for:** knowledge assistants, support copilots, and agent memory that need end‑to‑end latency and reliability.

Learn more in the Pinecone [documentation](https://docs.pinecone.io).

Key Use Cases

**RAG for LLMs:** high‑recall retrieval over enterprise content to ground model responses.

**Semantic product search:** relevance‑first shopping and catalog discovery.

**Personalization & recommendations:** vector similarity for content and product ranking.

**Customer support copilots:** instant retrieval of policies, KB articles, and troubleshooting steps.

**Agent memory:** durable, queryable long‑term memory for autonomous and workflow agents.

Architecture & Capabilities

**Vector indexing:** optimized for approximate nearest neighbor (ANN) search at scale.

**Hybrid retrieval:** blend dense embeddings with sparse signals for balanced precision/recall.

**Metadata‑aware results:** filter by product, region, role, compliance policy, and more.

**Namespaces for multi‑tenancy:** manage millions of small, isolated indexes across tenants.

**Caching layer:** serve repeat queries and frequent contexts with lower latency and cost.

**Operational simplicity:** serverless model removes cluster sizing, failover, and patching overhead.

Security, Privacy, and Compliance

**Certifications:** SOC 2 and ISO 27001.

**Regulatory support:** GDPR and HIPAA considerations for sensitive data.

**Isolation controls:** multi‑tenant namespaces and metadata policies to enforce data boundaries.

Pricing & Editions

**Starter (Free):** begin prototyping without upfront cost.

**Standard:** usage‑based with a modest monthly minimum and trial credits.

**Enterprise:** SLAs, advanced controls, and support for large‑scale, mission‑critical workloads.

For details, see Pinecone’s [documentation](https://docs.pinecone.io) or contact sales via the [Pinecone](https://www.pinecone.io) website.

Integrations & Ecosystem

Model and embedding providers: [OpenAI](https://openai.com), [Cohere](https://cohere.com), [Voyage AI](https://www.voyageai.com)

Frameworks and toolkits: [LangChain](https://www.langchain.com), [LlamaIndex](https://www.llamaindex.ai)

Data and analytics: [Snowflake](https://www.snowflake.com), [Databricks](https://www.databricks.com)

Cloud platforms: [AWS](https://aws.amazon.com), [Google Cloud](https://cloud.google.com), [Microsoft Azure](https://azure.microsoft.com)

Ideal Buyers and Teams

**Product & Search Teams:** deliver semantic, hybrid search with strong filters and latency SLAs.

**ML/AI Platforms:** standardize vector storage and retrieval for multiple LLM apps.

**Support & Success:** power knowledge copilots that reduce handle time and improve CSAT.

**Data & Engineering:** consolidate agent memory and RAG pipelines without managing infra.

Why Pinecone Stands Out

**Production‑grade performance:** consistent low latency at billion‑vector scale.

**Serverless operations:** reduced DevOps burden and faster iteration cycles.

**End‑to‑end RAG enablement:** Pinecone Assistant streamlines ingestion through response streaming.

**Enterprise trust:** robust compliance posture with multi‑tenant architecture.

Getting Started

1. Create an account on [Pinecone](https://www.pinecone.io).

2. Review the quickstarts in the [documentation](https://docs.pinecone.io).

3. Choose your path:

Use the **Pinecone Assistant** to stand up chat/agent apps quickly.

Integrate directly via SDKs with frameworks like [LangChain](https://www.langchain.com) or [LlamaIndex](https://www.llamaindex.ai).

4. Move from **Starter** to **Standard** or **Enterprise** as your scale and SLA needs grow.

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