For developers building AI-native products, Pinecone is a serverless vector database that indexes embeddings for low-latency semantic search, powering the retrieval layer inside production AI applications at companies like Adobe, Cisco, and HubSpot.
Presence & Market Position
#23 of 103
GTM Developer Tools
▲ 91 60-day move
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Pinecone occupies the position of infrastructure vendor turned knowledge layer for AI agents: a vector database that has expanded into retrieval filtering, an agent-facing knowledge engine, and a marketplace of ready-built knowledge applications, aimed at enterprises trying to get reliable context in front of production AI systems. It holds the top spot in its category and has been climbing fast in the broader conversation. That conversation is dense and practitioner-heavy: agencies and builders walking through their full AI stack routinely name it as the vector-search or RAG layer sitting alongside CRM, enrichment, and automation tools, and operators describe using it as the backing store for internal search over their own content libraries.
Neon
Convex
Qdrant
LanceDB
WeaviateDuolingo, Adobe, Cisco, GoDaddy, HubSpot, Zapier, Workday, Gong, ZoomInfo, Asana
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Business Profile
Pinecone was founded in 2019 by Edo Liberty and built the category around a serverless vector database for production AI retrieval. The company has raised $138M and was last valued at $750M as of 2023, reporting $14M in annual recurring revenue in 2025 against a customer base that includes Adobe, Cisco, HubSpot, and Duolingo. In September 2025, Liberty moved from CEO to Chief Scientist, handing the role to Ash Ashutosh, a longtime enterprise infrastructure executive, to lead the next phase of growth while Liberty focuses on the company's research direction. The company now employs 135 people.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Pinecone's agent build-out runs from an API and SDK to full MCP support, including dedicated MCP servers for search and documentation and official plugins for agentic coding tools like Claude Code, Cursor, Copilot, and Codex. In 2026 it extended upward with Pinecone Nexus, a knowledge engine that compiles an organization's documents into a structured layer AI agents query directly through KnowQL rather than re-retrieving raw documents on every call.
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