Integrations / Pinecone

Connect

Pinecone

with ToolJet

ToolJet makes it easy to create internal tools, search interfaces, and AI dashboards on top of your Pinecone vector data, without writing backend code.

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Available actions with ToolJet and Pinecone integration

ToolJet's integration with Pinecone supports various operations:

Query vector index

Search your Pinecone index using vector embeddings. Retrieve the top-k most similar vectors and return associated metadata, namespace, and score.

Fetch index stats

Get detailed statistics for your index, including vector count, dimension, and namespace-level data usage.

Update vectors

Update existing vectors in your index with new values or metadata using their unique IDs.

Delete vectors

Remove one or more vectors from your index by specifying their IDs.

Describe index

Retrieve metadata about the structure and configuration of a specific index.

Fetch namespaces

List all namespaces present in a given Pinecone index.

Why use ToolJet with Pinecone

AI-powered app building

Build internal tools, workflows, and AI agents in hours using plain English. Go from idea to production with AI-generated apps, data models, and instant debugging.

Enterprise-grade security and compliance

Stay secure with SSO, RBAC, audit logs, encryption, and compliance standards like SOC2, ISO 27001, and GDPR. Deploy your way: cloud, on-prem, or hybrid.

Production-ready database and integrations

Skip setup hassles with instant PostgreSQL and pre-built integrations for AI, databases, storage, and APIs.

Components and environment management

Speed up development with 60+ pre-built components and manage releases across dev, test, and production environments.

Flexible development options

Use no-code visual builders, or dive into low-code, and switch seamlessly as your needs evolve. You have full control, and there is no lock-in.

JavaScript and Python

Write custom logic and data transformations using JavaScript or Python, flexible scripting built right in.

Explore more AI integrations

Frequently asked questions

1. What is Pinecone AI?

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Pinecone AI is a managed vector database designed for building high-performance AI applications. It allows developers to store, index, and search vector embeddings efficiently, enabling use cases like semantic search, recommendation systems, and Retrieval-Augmented Generation (RAG).

2. What does Pinecone.io do?

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Pinecone lets you perform similarity searches on vector data in real time. It handles indexing, storage, and retrieval at scale, making it ideal for AI/ML-powered apps that rely on embeddings from models like OpenAI, Cohere, or Hugging Face.

3. How much does Pinecone cost?

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Pinecone offers a usage-based pricing model. You’re charged based on index storage, vector count, and request volume. They offer a free tier for testing and small-scale projects, while paid plans scale based on resource usage. You can find detailed pricing at pinecone.io/pricing.

4. Is Pinecone free to use?

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Pinecone offers a free plan that includes a single pod and limited compute and storage, ideal for prototyping or small apps. As your usage grows, you can upgrade to a paid plan with more pods, higher throughput, and additional storage.