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
#29 of 122
GTM Developer Tools
▲ 1 60-day move
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Pinecone is positioning its database as the governed retrieval layer for production agents, expanding semantic search with full-text retrieval in the same index and a knowledge layer agents can query directly. It has a visible place in GTM developer-tool conversation, where practitioners describe it as infrastructure for RAG, searchable company knowledge, and context systems behind content and outbound workflows. Recent discussion also centers on how retrieval fits into broader agent stacks, while Pinecone's product updates focus on combining literal and semantic search.
Neon
Qdrant
Convex
Chroma
LanceDBDuolingo, 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 has made its retrieval layer callable through API, SDK, CLI, and MCP surfaces. Its recent work pairs vector and full-text search in one index, while Nexus provides a governed knowledge layer for agent queries. Cultivar, its open-source evals library for agent docs and skills, extends the work from retrieval into evaluating how agents use the context they receive.
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