What can an AI agent do with Pinecone?

A Pinecone AI agent can query your indexes for semantically similar results, fetch or delete vectors by ID, upsert new embeddings with metadata, list and describe all indexes in your project, and monitor index health, all automatically on a schedule or triggered by events. Write actions like upserting or deleting always require your approval.

Do I need to provide embeddings myself, or can the AI agent generate them?

You provide the embedding model - your agent handles the Pinecone operations. Pair it with an OpenAI or HuggingFace integration to generate embeddings within the same workflow before upserting them into Pinecone.

Can my AI agent query across multiple indexes or namespaces?

Yes. You can instruct your agent to query specific indexes and namespaces in a single task, compare results across them, and aggregate or filter the output before returning it to you.

Is my vector data stored outside of Pinecone?

No. Vectors and metadata are only read or written during task execution and are not persisted anywhere outside your Pinecone account. Only task outputs such as query results or reports are saved to your run history.

Developer tools

Pinecone, run by an agent.

An AI agent that queries, manages, and monitors your Pinecone vector database.

Connect Pinecone Book a demo

What needs your approval

Pinecone never changes anything without you.

Anything that creates, edits or deletes in Pinecone waits for your approval. Approve a recurring task once and it runs unattended after that.

Connecting Pinecone

About 5 minutes

Auth: API key
Setup: About 5 minutes

Where to get access

Copy your API key from the Pinecone console under API Keys.

app.pinecone.io

Example tasks

Real work people hand to an agent that uses Pinecone.

run nightly embedding sync jobs that upsert new documents into a RAG index and report drift
query a product catalog index to power real-time semantic search and surface low-relevance results for review
monitor index fill rate and alert when a namespace is approaching capacity
automate cleanup of stale vectors by deleting entries older than a retention threshold