Optical Character Recognition (OCR) is essential for automating data extraction from PDFs and image documents into business software. In Zapier, alternatives typically fall into two categories: data extraction automation tools that include OCR as a feature, and tools focused solely on OCR functionality. This article explores these options and provides a practical example of automating data extraction from documents.
Optical character recognition (OCR) is a key technology for document data extraction. In the past, implementing accurate OCR into document workflows was often too complex and expensive for small and medium-sized businesses. Today, AI-powered no-code OCR tools with user-friendly interfaces and pre-built integrations for automation platforms like Zapier allow SMBs to leverage the best OCR tools at a much lower entry point.
Cradl AI combines LLMs with its own AI models to extract data from any document layout, quickly deployable with minimal setup. Its built-in error-handling ensures 100% accurate data extraction at any scale.
Parseur offers an AI-based OCR engine for flexible data extraction from PDFs and text documents. It's supports automatic parsing without templates, ensuring quick setup and reliable automation for OCR tasks.
Docparser is an OCR tool that combines zonal OCR and AI to extract structured data from PDFs, Word documents, and images.
Docparser's Zapier integration
Zapier doesn't offer a direct integration for using ChatGPT for structured data extraction, requiring a workaround. This method combines Google’s OCR with ChatGPT’s text parsing abilities but involves a complex Zap workflow. A simpler alternative is to use Cradl AI, which combines LLMs with its own AI models.
PDF.co offers OCR for document data extraction using a template-based approach. It works well for fixed layouts but may require separate templates for different document types.
Let’s see an actual Zapier automaton example of how to extract receipt data from emails to Google Sheets by using Cradl AI as our data extraction tool and integrating with Zapier.
Before starting, make sure you’ve created a free Cradl AI account.
Once you're logged in, create your first AI model in just a few clicks. You can either clone a template for common documents like receipts and invoices, or build a custom model from scratch.
In this tutorial, I’ll clone the receipt model. If you're working with invoices, check out our Zapier guide to extracting invoice data from emails to Sheets.
To process your first document, simply upload it, and your AI model will automatically extract the data.
Cradl AI's models are highly accurate but will flag uncertain predictions for manual review instead of automatically validating the document. Any corrections you make contribute to retraining and improving the model over time. Once everything looks accurate, click Validate.
In this example, the receipt didn’t include a VAT amount, so the AI model left it blank, with 88% confidence that no VAT was present.
Connect your Cradl AI model to Zapier to automate data extraction and use the data in thousands of apps. If you’re new to Zapier, sign up and create a Zap.
Search for Cradl AI among the Zapier's integrations, and choose Cradl AI's Document Parsing Completed trigger. This will activate a Zap after completing the document validation step we performed in the step above.
We’ll use Google Sheets to store our extracted data, but Excel works fine too. Just make sure your spreadsheet is hosted in a cloud service that integrates with Zapier, like Google Drive or Microsoft OneDrive.
Create a new sheet and add headers, typically matching the fields you’re extracting. In Google Sheets, simply type the headers into the topmost cells.
Because we'll be adding one row to our spreadsheet for each document, we'll use Google Sheets's Create Spreadsheet Row action.
If you need to add multiple rows at once (e.g., for purchased items), check out our guide on extracting data from PDF tables and exporting it to Excel via Zapier.
When mapping Cradl AI's extracted fields to your spreadsheet headers, you’ll see many options beyond the ones in your headers.
99% of the time, you're looking for the fields prefixed with Validated Predictions and suffixed with Value, like Validated Predictions Purchase Date Value or Validated Predictions Total Amount Value. The other fields are either metadata or original values that haven’t been validated.
Upload your documents to Cradl AI and wait for the model to process them. If the AI is uncertain about any predictions, it will flag them for manual review. Make any adjustments, click Validate, and the entire data extraction workflow—from Cradl AI to Zapier to Google Sheets—will run automatically.
If you would like a version of this tutorial that does into more detail, this video has got you covered.
We’ll help get you started with your document automation journey.
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