---
title: Vercel Pinecone Integration
product: vercel
url: /docs/agent-resources/integrations-for-models/pinecone
type: how-to
prerequisites:
  - /docs/agent-resources/integrations-for-models
  - /docs/agent-resources
related:
  []
summary: Learn how to add Pinecone connectable account integration with Vercel.
install_vercel_plugin: npx plugins add vercel/vercel-plugin
---

# Vercel Pinecone Integration

 is a [vector
database](/kb/guide/vector-databases) service that handles the storage and search
of complex data. With Pinecone, you can use machine-learning models for content
recommendation systems, personalized search, image recognition, and more. The
Vercel Pinecone integration allows you to deploy your models to Vercel and use
them in your applications.

## Use cases

You can use the Vercel and Pinecone integration to power a variety of AI applications, including:

- **Personalized search**: Use Pinecone's vector database to provide personalized search results. By analyzing user behavior and preferences as vectors, search engines can suggest results that are likely to interest the user
- **Image and video retrieval**: Use Pinecone's vector database in image and video retrieval systems. They can quickly find images or videos similar to a given input by comparing embeddings that represent visual content
- **Recommendation systems**: Use Pinecone's vector database in e-commerce apps and streaming services to help power recommendation systems. By analyzing user behavior, preferences, and item characteristics as vectors, these systems can suggest products, movies, or articles that are likely to interest the user

## Deploy a template

You can deploy a template to Vercel that includes a pre-trained model and a sample application that uses the model:

## More resources


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[View full sitemap](/docs/sitemap)