OCR Web Service is a cloud-based optical character recognition platform that converts documents and images into machine-readable text.
Enhance your document processing with AI Agents that can automatically extract insights and take action.
OCR Web Service excels at converting documents and images into machine-readable text. Relevance AI transforms this capability into intelligent AI Agents that can automatically extract, analyze and act on document data at scale.
Seamless Data Transformation
Effortlessly converts documents into structured data for immediate use.
Enhanced Decision-Making
Provides actionable insights through automated data analysis.
Rapid Workflow Automation
Streamlines processes by automating repetitive tasks and document handling.
Relevance AI gives you access to OCR Web Service's document processing capabilities within your AI Agent workflows.
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 Relevance AI account
- An Airtable account with access to the base and table you'd like to use
- Authorization (you'll connect securely using OAuth—no sensitive info stored manually)
Security & Reliability
The integration leverages secure OAuth authentication to protect OCR Web Service data access, with Relevance AI managing API operations seamlessly in the background. Built-in OCR processing and image format validation ensure accurate text extraction across varied document types.
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.
Best Practices for Non-Technical Users
To get the most out of the OCR Web Service + Relevance AI integration without writing code:
- Optimize your images: Use clear, high-resolution images in supported formats (PNG, JPEG, PDF).
- Configure OCR settings: Adjust language and recognition parameters for best accuracy.
- Manage API requests: Stay within rate limits and use appropriate HTTP methods for each operation.
- Handle responses properly: Monitor status codes and implement error handling for failed requests.
- Validate results: Test OCR accuracy on sample documents before processing large batches.
