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.
Integrations

Supercharge 0CodeKit with Relevance AI

MonkeyLearn is a powerful text analysis platform that allows users to perform classification and extraction tasks through a simple API. With Relevance AI, you can leverage these capabilities to create dynamic workflows that utilize AI Agents for smarter data insights.

Give your AI Agents 0CodeKit Superpowers

MonkeyLearn provides robust text classification and extraction capabilities. Relevance AI amplifies these features by enabling intelligent AI Agents to automate and optimize your data processing tasks.

Intelligent Text Processing Mastery

Empowers the AI agent with advanced NLP capabilities to understand and process text data with high accuracy and speed

Automated Insight Generation

Enables rapid extraction of valuable patterns and trends from large volumes of text data for informed decision-making

Custom Entity Recognition

Develops specialized knowledge extraction capabilities tailored to specific business domains and requirements

Tools

Equip AI Agents with the 0CodeKit Tools they need

Relevance AI seamlessly integrates with MonkeyLearn to enhance your text analysis workflows.

0codekit - 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
0codekit - Read Barcode
A utility for extracting and interpreting barcode data from images by processing an image URL containing QR codes or other barcode formats
0codekit - 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
0codekit API Call
Description
Make an authorized request to a 0codekit 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 0codekit 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.

Security & Reliability

The MonkeyLearn integration leverages a straightforward API interface to enable robust text analysis capabilities, allowing you to automate text classification and extraction tasks seamlessly. With secure OAuth-based authentication, only authorized workflows can access your MonkeyLearn data, ensuring data integrity and security.

Relevance AI manages API operations (such as POST requests for text classification and extraction) in the background, so you can focus on analyzing results without worrying about errors, formatting, or rate limits. Built-in validation and type conversion ensure that your workflows run smoothly, even when dealing with varying data formats.

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.

Get Started

Best Practices for Non-Technical Users

To get the most out of the 0CodeKit + Relevance AI integration without writing code:
  • Start with a clear setup: Ensure your 0CodeKit account is properly configured with the necessary OAuth credentials and permissions.
  • Utilize example code: Leverage the provided code snippets for PDF compression and barcode reading to jumpstart your integration.
  • Validate inputs: Always check your input parameters for correctness before making API calls to avoid unnecessary errors.
  • Test with sample data: Run your automations using test PDFs and images to ensure everything works smoothly before going live.
  • Monitor API usage: Keep an eye on your API calls to avoid hitting rate limits, and implement caching where appropriate.