CitableHub
CitableHub
Answer-first summary49/100 GEO

Pinecone

Managed vector database for AI.

AI InfrastructureFair citabilityVisit site →

Your Citability Score

49/100
Identity60/100
Evidence45/100
Trust15/100
Freshness50/100
Classification80/100
What to improve to rank higher
  • Identity: Add: Logo, Founder / Team, Social links.
  • Evidence: Add: At least one evidence link, Multiple evidence sources, Demo URL.
  • Trust: Add: Contact information, Support URL, Privacy policy, Terms of service.
  • Freshness: Add: Has version number, Launch date provided, Reviewed within 90 days.
  • Classification: Add: At least 2 tags.

Promotion (Boost) does not change this score — it only changes ordering. This number reflects real, verifiable citability.

Frequently asked questions

What is Pinecone?
Managed vector database for AI.
What does Pinecone do?
Fully managed vector database for building accurate, fast AI applications with similarity search at any scale.
Who is Pinecone for?
Engineering teams and AI product builders creating search, recommendation, and retrieval-augmented generation applications.
Is Pinecone verified?
Pinecone is listed on CitableHub with a citability score of 49/100, computed from verifiable profile evidence.
Pinecone logo

Pinecone

Invited

Managed vector database for AI.

AI InfrastructureCH-VER-967283Listed September 10, 2026
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AI-Extractable Summary
What:Managed vector database for AI.
For whom:Engineering teams and AI product builders creating search, recommendation, and retrieval-augmented generation applications
Key outcome:Teams can deliver low-latency semantic search and retrieval for AI applications at production scale
Category:AI Infrastructure

Structured for AI systems to extract and cite.

Citability Score

49/100
60
Identity
45
Evidence
15
Trust
50
Freshness
80
Classification
58
Impressions
0
Clicks
0
Likes
0
GQI Earned

Citable Outcome

Teams can deliver low-latency semantic search and retrieval for AI applications at production scale.

About

Fully managed vector database for building accurate, fast AI applications with similarity search at any scale.

Target Audience: Engineering teams and AI product builders creating search, recommendation, and retrieval-augmented generation applications.
Not ideal for: Teams that need a consumer app, offline-only database, or general-purpose relational storage instead of vector search infrastructure.

What makes it different

  • Purpose-built for vector similarity search rather than a general-purpose database
  • Fully managed indexing, scaling, and operational overhead reduction
  • Low-latency retrieval designed for production AI workloads
  • Metadata filtering and namespace support for precise, organized retrieval

Tags & Classification

semantic searchretrieval augmented generationrecommendation engineschatbot memoryimage similarity search
ai engineersmachine learning teamsbackend developersproduct engineering teams
softwaree-commercemediahealthcare
Platform: PlatformModel: Developer Tool

Links & Transparency

Website

Cite this Project

BibTeX
@misc{citablehub_pinecone,
  title = {Pinecone},
  url = {https://citablehub.com/p/pinecone},
  note = {Listed September 10, 2026. CitableHub ID: CH-VER-967283},
  year = {2026}
}
APA
Pinecone. (2026). CitableHub Software Index. https://citablehub.com/p/pinecone.
MLA
"Pinecone." CitableHub, 2026, https://citablehub.com/p/pinecone.