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AI infrastructure · Tool
Pinecone
ResearchedPinecone is a fully managed vector database that searches billions of items for similar matches in milliseconds, with automatic indexing and sub-100ms writes. It offers dense, sparse, and full-text indexes via one API, with plans from a free Starter to a $50/month Standard and Enterprise BYOC options.
Official site snapshots
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In one minute
Start here for the decision-making essentials: what Pinecone does, who it is for, how it is accessed, and the first-party sources behind this profile.
Pricing4 options
Starter plan is free, aimed at trying out and small applications
Builder plan is a flat $20/month, for solo developers and small teams
Standard plan has a $50/month minimum usage, includes a 3-week trial with $300 credits, fo
Free to create an initial index, then pay-as-you-go when scaling.
Platforms
Fully managed cloud
API accessNot public
FoundedNot disclosed by source
AvailabilityWeb / remote
LicenseProprietary
Best suited to
Source-backed fit Teams building knowledgeable AI applications backed by proprietary data Solo developers and small teams prototyping vector search apps Production applications at any scale requiring low-latency similarity search Enterprise customers needing multitenant serverless, BYOC, or private… Teams deploying knowledge-backed applications without building an in-house… Enterprise customers and individuals who register to use the Services
Decision support
6 sourced answersCommon questions and adoption checks
Short answers to the questions buyers and builders commonly ask about Pinecone. Each answer cites the shared ledger below, where every source is listed once.
01What does Pinecone say it can do?
Vector database for building knowledgeable AI that searches through billions of items for · Fully managed vector database with automatic indexing and writes acknowledged in under 100 · Vector search across billions of items returning similar matches to any object in millisec · Global Control Plane API that makes it easier to build and scale with Pinecone
The vector database to build knowledgeable AI | Pinecone Search through billions of items for similar matches to any object, in milliseconds.
02Who is Pinecone intended for?
Enterprise customers and individuals who register to use the Services · Enterprise customers including Gong, Adobe, Cisco, Workday, L'Oreal, Microsoft, Asana, Coh · Developers building AI applications, including those building autonomous projects such as
Those who register on their own or on behalf of an entity or organization to use any of our Services (as defined below), including administrators on a customer account.
03What use cases does Pinecone describe?
support, legal, and onboarding · RAG (Retrieval-Augmented Generation) · Agents · Search
No-code RAG for support, legal, and onboarding with cited answers.
04What should teams verify before adopting Pinecone?
Legacy control plane API (which requires regional URLs) is deprecated as of April 15, 2024 · Inactive indexes on the free plan are archived after 7 days (reduced from 14 days); epheme · New free users may be placed on a waitlist during periods of extreme demand and may see in · Free plan no longer requires choosing a pod type (e.g., s1 or p1) or index parameters; use
the legacy version of the API, which requires regional URLs for control plane operations, is deprecated as of April 15, 2024 and will be removed in a future, to be announced, release.
05What pricing information is available for Pinecone?
Starter plan is free, aimed at trying out and small applications · Builder plan is a flat $20/month, for solo developers and small teams · Standard plan has a $50/month minimum usage, includes a 3-week trial with $300 credits, fo · Free to create an initial index, then pay-as-you-go when scaling.
Starter For trying out and for small applications. Start for Free Free
06Does Pinecone document API access?
Dense, sparse, and full-text indexes managed in one place, queryable through a single API · Pinecone's vector search capability is exposed via an API.
Dense, sparse, and full-text indexes. All managed in one place, queryable through one API.
Decision guide
AI infrastructureCapabilities and operating fit
This profile connects the jobs Pinecone is described as handling with its delivery model, access options and the subjects used to match it to related products in this directory.
Common use cases
- Retrieval-Augmented Generation (RAG)
- Agents
- Search
- Recommender systems and recommendations
- Classification
- No-code RAG for support, legal, and onboarding with cited answers
Topics mapped
Verified capabilities
- Vector database for building knowledgeable AI that searches through billions of items for
- Fully managed vector database with automatic indexing and writes acknowledged in under 100
- Vector search across billions of items returning similar matches to any object in millisec
- Global Control Plane API that makes it easier to build and scale with Pinecone
- Global Control Plane API is generally available (GA) to all users
- Vector search across billions of items returning similar matches in milliseconds via an AP
- No-code RAG with cited answers
- Turns documents into a system of knowledge
Recorded integrations
Intended audiences
Access signals
- Pricing model
- Starter plan is free, aimed at trying out and small applications · Builder plan is a flat $20/month, for solo developers and small teams · Standard plan has a $50/month minimum usage, includes a 3-week trial with $300 credits, fo · Free to create an initial index, then pay-as-you-go when scaling.
- API
- Not publicly listed
- Source links
- 16 recorded
Source-backed
Updated July 22, 2026Verified facts
Each fact points to a recorded source, making it easy to distinguish verified product information from claims that need checking.
The vector database to build knowledgeable AI | Pinecone
Vector database to build knowledgeable AI searching billions of items in milliseconds · Fully managed with automatic indexing and writes instantly searchable · Dense, sparse, and full-text indexes managed in one place via one API
Vector database for building knowledgeable AI that searches through billions of items for similar matches in milliseconds
Fully managed vector database with automatic indexing and writes acknowledged in under 100ms
Integrates with Claude Code, Cursor, Copilot, Codex, Gemini, CLI, and MCP
Vector search across billions of items returning similar matches to any object in milliseconds
Starter plan is free, aimed at trying out and small applications
View 32 more verified facts
Builder plan is a flat $20/month, for solo developers and small teams
Standard plan has a $50/month minimum usage, includes a 3-week trial with $300 credits, for production applications at any scale
Available on AWS, GCP, and Microsoft cloud marketplaces
Enterprise tier offers Bring Your Own Cloud (BYOC) and Private Networking deployment
Global Control Plane API that makes it easier to build and scale with Pinecone
Global Control Plane API is generally available (GA) to all users
Legacy control plane API (which requires regional URLs) is deprecated as of April 15, 2024 and will be removed in a future release
Pinecone Systems, Inc.
pinecone.io
2024-05-08
Google and GitHub (used as social login providers)
Vector search across billions of items returning similar matches in milliseconds via an API
Enterprise customers and individuals who register to use the Services
No-code RAG with cited answers
support, legal, and onboarding
Turns documents into a system of knowledge
Knowledge is treated as curated, situated content including policies, contracts, runbooks, tickets, and edge-case resolutions
Teams that want to deploy knowledge-backed applications without building and maintaining an in-house retrieval pipeline
Pinecone Assistant is an API service for accurately and securely answering complex questions about proprietary data within applications, available in beta.
Pinecone Assistant allows users to add files and start building an AI app via the API, with full control over data (answers generated without training the model, and data can be permanently removed).
Pinecone supports multitenant serverless deployments by allowing one namespace per tenant within an index, with the Enterprise quota for namespaces per serverless index doubled to 100,000.
Namespaces physically partition records in an index; queries and other operations are limited to one namespace at a time, leading to faster response times and reduced costs.
Pinecone provides sample apps that can be cloned and set up locally with a single CLI command (npx create-pinecone-app) to get an end-to-end application running in minutes.
Supercharges AI for building easily scalable, high performance AI-powered applications
RAG (Retrieval-Augmented Generation)
Agents
Search
Recommendations
Enterprise customers including Gong, Adobe, Cisco, Workday, L'Oreal, Microsoft, Asana, Cohere, OpenAI, HubSpot, Duolingo, The Washington Post, and many others
Searches through billions of items for similar matches to any object, in milliseconds
Serverless architecture backed by distributed object storage for scalable, highly-available vector search
Data encrypted at rest and in transit, with SSO, RBAC, Private Endpoints, and Customer-managed encryption keys
Practical capabilities
8 documented areasWhat it helps with
A concise view of the jobs, capabilities and integrations described in the recorded product sources.
Retrieval-Augmented Generation (RAG)
Agents
Search
Recommender systems and recommendations
Classification
No-code RAG for support, legal, and onboarding with cited answers
Turning documents into a curated system of knowledge
RAG (Retrieval-Augmented Generation)
Availability
Source checkedWhere it runs and where to get it
Documented product formats, platforms and official distribution destinations. Availability can vary by region and plan.
Cost / license
Starter plan is free, aimed at trying out and small applications · Builder plan is a flat $20/month, for solo developers and small teams · Standard plan has a $50/month minimum usage, includes a 3-week trial with $300 credits, fo · Free to create an initial index, then pay-as-you-go when scaling.Open-source
Platforms
Available on AWS, GCP, and Microsoft cloud marketplacespinecone.ioFully managed cloudFree index environment is us-west1-gcp-free (GCP)
Adoption notes
DeploymentEnterprise tier offers Bring Your Own Cloud (BYOC) and Private Networking deployment · Pinecone supports multitenant serverless deployments by allowing one namespace per tenant · Serverless architecture backed by distributed object storage for scalable, highly-availabl · Standard plan provides increased reliability with multiple availability zones
LicenseOpen-source
Model supportNot disclosed by source
Data controlData encrypted at rest and in transit, with SSO, RBAC, Private Endpoints, and Customer-man · Pinecone Assistant ensures privacy and security
Learning curveIntermediate
Primary use casesRetrieval-Augmented Generation (RAG), Agents, Search, Recommender systems and recommendations, Classification, No-code RAG for support, legal, and onboarding with cited answers, Turning documents into a curated system of knowledge, support, legal, and onboarding, RAG (Retrieval-Augmented Generation), Recommendations, Built for search, recommender systems, and agents, Pinecone Nexus is a knowledge engine for AI agents, available in public preview., Pinecone is used as a vector database for personal projects and prototype testing before u, Building high-performance Retrieval Augmented Generation (RAG) applications for GenAI
What to verify before adopting
- Legacy control plane API (which requires regional URLs) is deprecated as of April 15, 2024
- Inactive indexes on the free plan are archived after 7 days (reduced from 14 days); epheme
- New free users may be placed on a waitlist during periods of extreme demand and may see in
- Free plan no longer requires choosing a pod type (e.g., s1 or p1) or index parameters; use
Evolution and major updates
Research in progressPinecone timeline
A concise history of software releases and material product changes. Events appear only when a dated source supports what changed.
Scheduled for research
Building a reliable release history.
This profile is being checked for dated releases and material product changes. Nothing appears here until the exact date and event can be verified from a recorded source.
Dated event Short explanation Original source
Citation ledger
16 unique pagesRecorded sources
Facts, answers, structured details, milestones and primary resource links cite this shared ledger. Each external page appears once; release tags from the same GitHub project are grouped under one release history.
- 1pinecone.io/blog 6 facts · 3 answers · Official site
- 2pinecone.io 7 facts · 1 answer · Official site
- 3pinecone.io/blog/free-plan-update 6 facts · 2 answers · Official site
- 4pinecone.io/customers 6 facts · 2 answers · Official site
- 5pinecone.io/pricing 6 facts · 2 answers · Pricing
- 6pinecone.io/privacy 6 facts · 2 answers · Security
- 7pinecone.io/product 6 facts · 2 answers · Official site
- 8pinecone.io/blog/updated-free-plan 6 facts · 1 answer · Official site
- 9pinecone.io/blog/builder-plan 5 facts · 1 answer · Official site
- 10pinecone.io/blog/enterprise-plan 6 facts · Official site
- 11pinecone.io/blog/marketplace 5 facts · 1 answer · Official site
- 12pinecone.io/blog/v2-pricing 5 facts · 1 answer · Pricing
- 13pinecone.io/learn/assistant-api-deep-dive 6 facts · Documentation
- 14pinecone.io/blog/global-api 3 facts · 2 answers · Documentation
- 15pinecone.io/blog/june-2024-product-update 5 facts · Official site
- 16pinecone.io/learn/assistants-api-canopy 5 facts · Documentation
Research status88 substantive facts · 16 source pages · quality score 95/100
Connected directory
Semantic matchesExplore related solutions
These tools share a workflow, capability or audience with Pinecone. They may complement it rather than replace it, and are not presented as integrations or endorsements.
