Pinecone's mission is to make AI knowledgeable

Pinecone is the leading vector database for building
accurate and performant AI applications at scale in production.

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Pinecone helps power AI for the world’s best companies

At Cisco, we’re not only integrating generative AI capabilities throughout products for our customers, we’re also enabling our employees with the most cutting-edge technologies like Pinecone. By leveraging Pinecone’s industry-leading vector database on Google Cloud, our enterprise platform team built an AI assistant that accurately and securely searches through millions of our documents to support our multiple orgs across Cisco

Sujith Joseph

Principal Engineer, Enterprise AI & Search at Cisco

Customers

Start and scale seamlessly

Quickstart Guide

Docs

from pinecone import Pinecone, ServerlessSpec

# Create a serverless index
# "dimension" needs to match the dimension of your embedding model
pc = Pinecone(api_key="YOUR_API_KEY")

pc.create_index(name="example-index", dimension=1024, 
    spec=ServerlessSpec(cloud='aws', region='us-east-1') 
)

# Target the index
index = pc.Index("example-index")

# Embed your data
vector = pc.inference.embed(
    model="multilingual-e5-large",
    inputs=["The quick brown fox jumps over the lazy dog."],
    parameters={
        "input_type": "passage",
        "truncate": "END"
    }
)

# Upsert your vector embedding(s)
upsert_response = index.upsert(
  vectors=[
    {
        "id": "some_id", 
        "values": vector[0].values, 
        "metadata": { "description": "English pangram" }
    }
  ]
)

Choose a hosted model
or bring your own

Pinecone supports embeddings from any model or provider. Choose your preferred model or use the Inference API for fully managed embedding and reranking.

Model Gallery

Model	Company
pinecone-sparse-english-v0 Inference API	Pinecone
cohere-rerank-3.5 Inference API	Cohere
multilingual-e5-large Inference API	Microsoft
jina-embeddings-v3	Jina AI
text-embedding-3-large	OpenAI

Easily integrate with
your favorite tools

Pinecone is part of the developer-favorite AI stack. Easily integrate and build with your favorite cloud provider, data sources, models, frameworks, and more.

Integrations