Headquarters
New York, NYFounded
2019CEO / Founder
Edo LibertyEmployees
201-500Funding
Series C — $138MProducts
1 product listedAvg. AI Score
8.2/10Website
pinecone.io/Profile updated
Pinecone Systems Inc. is a cloud-native vector database company headquartered in New York, NY, founded in 2019 by Edo Liberty, a former head of Amazon AI Labs. The company provides a managed vector database service that allows developers to store and query high-dimensional vector embeddings generated by machine learning models, without managing underlying infrastructure.
Pinecone's primary product is its serverless vector database, which supports use cases such as retrieval-augmented generation (RAG), semantic search, and recommendation systems. The platform is used by engineering teams building AI-powered applications that require fast approximate nearest-neighbor search at scale. Pinecone integrates with major AI frameworks and model providers including OpenAI, Hugging Face, and LangChain.
The company raised a $100 million Series B round in April 2023 at a $750 million valuation, led by Andreessen Horowitz, following earlier rounds that brought total funding to approximately $138 million. Pinecone employs roughly 200-400 people. The company introduced a serverless pricing tier in early 2024, shifting from pod-based infrastructure to a consumption-based model.
All products by Pinecone Systems Inc. reviewed by our AI panel of experts.
Who Pinecone Systems Inc. competes with, and how they differ.
Open-source vector database with a self-hostable option alongside its managed cloud, appealing to teams wanting more infrastructure control than Pinecone's fully closed serverless model.
1 product reviewed on TopReviewedOpen-source, developer-first embedding database aimed at smaller-scale and prototyping use cases, with a lighter-weight footprint than Pinecone's enterprise-grade managed service.
1 product reviewed on TopReviewedEstablished search and analytics platform that added vector search capabilities to its existing Elasticsearch stack, targeting enterprises already invested in Elastic for logging and full-text search rather than AI-native vector workloads.
1 product reviewed on TopReviewedManaged cloud version of the open-source Milvus vector database, competing directly on large-scale, high-performance vector search with a more open, self-hostable architecture than Pinecone.
Vector search bolted onto MongoDB's general-purpose document database, targeting existing MongoDB customers who want to add semantic search without adopting a separate specialized vector database.
Enterprise search and personalization platform sold as a business application layer for e-commerce and support use cases, rather than a raw infrastructure component like Pinecone.
1 product reviewed on TopReviewedBrowse multi-perspective AI panel reviews across hundreds of AI tools, agents, and platforms. Find the right software with insights from CTO, Developer, Marketer, Finance, and User perspectives.