What can an AI teammate do with Pinecone?

A Pinecone AI assistant 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 teammate generate them?

You provide the embedding model - your teammate 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 teammate query across multiple indexes or namespaces?

Yes. You can instruct your teammate 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

AI Teammate for Pinecone

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

Your AI teammate for Pinecone queries indexes for semantically similar vectors, upserts new embeddings, fetches or deletes vectors by ID, and monitors index health and statistics. An ideal AI assistant for RAG pipelines, semantic search, and AI-powered recommendation systems. Write actions always require your approval.

Vector search is the backbone of modern AI applications, but managing indexes, debugging retrieval quality, and keeping embeddings up to date is tedious. A Pinecone AI teammate handles the operational side - querying, upserting, and inspecting your indexes, so you can focus on building.

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What your AI teammate can do with Pinecone

Read-only actions run automatically. Write actions require your approval.

Read-only actions

query index

Search an index for the most similar vectors to a given embedding

fetch vectors

Retrieve specific vectors by ID from an index

list indexes

List all indexes in your Pinecone project with their status

describe index

Get detailed stats and configuration for a specific index

Write actions (require approval)

upsert vectors

Insert or update vectors and their metadata in an index

delete vectors

Remove specific vectors or all vectors in a namespace from an index

create index

Provision a new Pinecone index with specified dimensions and metric

Example workflows with Pinecone

Real tasks you can run on a schedule or on demand.

task

run nightly embedding sync jobs that upsert new documents into a RAG index and report drift

task

query a product catalog index to power real-time semantic search and surface low-relevance results for review

task

monitor index fill rate and alert when a namespace is approaching capacity

task

automate cleanup of stale vectors by deleting entries older than a retention threshold

How to connect Pinecone

Create a free m8tes account.

Connect Pinecone

Click Connect and complete the OAuth flow or enter your API key.

Create a task

Give your AI teammate a task that uses Pinecone. It handles the rest.

Pinecone AI teammate: FAQ

Common questions about using an AI teammate with Pinecone.

Build an AI teammate for Pinecone

Connect Pinecone to an autonomous AI teammate that reads data, runs tasks on schedule, and delivers structured output.

AI teammates — all integrations
Build a teammate that uses Pinecone alongside your other tools.

Related integrations

Teams that use Pinecone also connect these.

OpenAI

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Anthropic

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Hugging Face

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GitHub

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