Agents@Work - See AI agents in production at Canva, Autodesk, KPMG, and Lightspeed.
Agents@Work - See AI agents in production at Canva, Autodesk, KPMG, and Lightspeed.
Watch now
Watch now
Integrations

Supercharge Kaggle with Relevance AI

Kaggle is a leading platform for data science and machine learning, offering datasets, code sharing, and competitions.

Enhance your data science capabilities with AI Agents that can leverage Kaggle's resources for automated analysis and decision-making.

Try for freeQuick Start

Give your AI Agents Kaggle Superpowers

Kaggle provides vast datasets and machine learning resources for data science projects. Relevance AI transforms these capabilities into intelligent AI agents that can analyze data, generate insights, and make automated decisions.

Data-Driven Insights

The agent harnesses Kaggle's extensive datasets to generate actionable insights.

Rapid Model Development

Accelerate the creation of predictive models using community-driven resources.

Real-Time Analytics

Utilize real-time data processing to make informed decisions swiftly.

Tools

Equip AI Agents with the Kaggle Tools they need

Relevance AI gives you access to Kaggle's extensive datasets and machine learning capabilities within your AI agent workflows.

Pre-Built Kaggle Tool Steps
Kaggle API Tool Steps
kaggle - Compress PDF
A tool for compressing PDF files by providing a URL to the source PDF and specifying the output filename, helping reduce file sizes while maintaining document quality
kaggle - Read Barcode
A utility for extracting and interpreting barcode data from images by processing an image URL containing QR codes or other barcode formats
kaggle - Read Barcode
A utility for extracting and interpreting barcode data from images by processing an image URL containing QR codes or other barcode formats
Name
kaggle API Call
Description
Make an authorized request to a kaggle API
Parameters
["OAuth Authentication", "Multiple HTTP Methods (GET, POST, PUT, DELETE, PATCH)", "Custom Headers", "Request Body Support", "Response Status Tracking"]
Use Case
A software development team uses kaggle API Call to automate their deployment process by making authenticated API requests to trigger builds and updates across their infrastructure. This integration streamlines their CI/CD pipeline by enabling secure, programmatic access to their development resources.
Try for free
Quick Start

Connect Kaggle to Relevance AI in minutes

What you’ll need

You don't need to be a developer to set up this integration. Follow this simple guide to get started:

  • A Kaggle account
  • A Relevance AI account with access to your datasets
  • Authorization (connect securely via API keys—no sensitive info stored manually)
Try for free
STEP 1

Open Relevance AI

Go to "Integrations" and select Kaggle from the available data science integrations.

STEP 2

Connect Your Kaggle Account

A secure pop-up will ask you to log in to Kaggle. This authorizes Relevance AI to make API requests on behalf of your Kaggle account and access your datasets and competitions.

STEP 3

Create a new tool

From the home page go to create a new tool. You can either use the Invent function or build from scratch.

STEP 4

Add Kaggle as a Step

Choose Kaggle from the list of tools, then select what API action you want to perform—like accessing datasets, submitting to competitions, or managing your Kaggle notebooks.

Security & Reliability

The integration leverages secure OAuth authentication to safely access your Kaggle datasets and APIs. Relevance AI manages API operations in the background, handling GET, POST, PUT, PATCH and DELETE requests automatically—so you can focus on analyzing data without worrying about implementation details.

Built-in validation ensures your workflows execute reliably when working with Kaggle's competition, dataset, and kernel APIs.

No training on your data

Your data remains private and is never utilized for model training purposes.

Security first

We never store anything we don’t need to. The inputs or outputs of your tools are never stored.

Try for free
Get Started

Best Practices for Non-Technical Users

Build your own Relevance AI Integration

Try for free
To get the most out of the Kaggle + Relevance AI integration without writing code:
  • Organize your datasets: Keep Kaggle datasets well-documented with clear metadata and descriptions.
  • Use API endpoints wisely: Choose the appropriate Kaggle API endpoints for your specific data needs.
  • Authenticate properly: Ensure your Kaggle API credentials are correctly configured and permissions are set.
  • Monitor API usage: Stay within Kaggle's API rate limits and implement proper error handling.
  • Version control: Track dataset versions and maintain consistent naming conventions for your workflows.

Free your team.
Build your first AI agent today!

If you're exploring Relevance AI for the first time or discovering new features, we'll quickly guide you to start doing great work immediately.

Try for freeRequest Demo
Free plan
No card required