Amazon Textract is a machine learning service that extracts text and data from scanned documents. Custom Queries is a feature that allows you to customize the extraction of information from non-standard documents like checks. By customizing the feature, you can achieve greater accuracy in data extraction without the need for ML expertise or infrastructure management.
Customize Amazon Textract with Custom Queries for Business-Specific Documents
Amazon Textract is a powerful machine learning (ML) service that automatically extracts text, handwriting, and data from scanned documents. With the Queries feature, you can extract specific information from complex documents using natural language. But what about business-specific, non-standard documents like auto lending contracts, checks, and pay statements? That’s where Custom Queries comes in.
Custom Queries: Tailored Extraction for Your Unique Documents
Custom Queries allows you to customize the Queries feature for your specific document types. By training an adapter with your sample documents, you can teach Amazon Textract to recognize the unique terms, structures, and key information in your documents. This customization improves extraction accuracy, reduces the need for manual intervention, and meets your downstream processing needs with greater precision.
What’s more, Custom Queries is easy to integrate into your existing Textract pipeline. You can continue to benefit from the fully managed intelligent document processing features of Amazon Textract without the need for ML expertise or infrastructure management.
Practical Use Case: Extracting Data from Checks
Let’s explore how Custom Queries can improve data extraction accuracy in a challenging real-world scenario: extracting data from checks. Checks can vary greatly in layout, with differences in payee’s name, payment amount, date, and more. These variations make data extraction complex and often require manual verification and validation processes, increasing costs and time.
With Custom Queries, you can customize the pre-trained Queries feature to handle these variations. By creating an adapter and training it with sample checks, you can achieve high data extraction accuracy for the specific layouts you process.
The Custom Queries Workflow
Here’s a step-by-step overview of the Custom Queries workflow:
- Evaluate Queries performance on your documents using the Textract console.
- If errors occur, create an adapter and annotate sample documents using the AWS Management Console.
- Train the adapter to improve extraction accuracy.
- Evaluate performance metrics such as F1 score, precision, and recall.
- Programmatically test the adapter using the AnalyzeDocument API.
By following this workflow, you can customize Amazon Textract to accurately extract data from your business-specific documents.
Benefits of Custom Queries
Custom Queries offers several benefits:
- Enhanced document understanding: Custom Queries reduces reliance on manual reviews, audits, and enables more reliable automation for intelligent document processing workflows.
- Faster time to value: You can generate an adapter within hours, without waiting for a pre-trained model update.
- Data privacy: Custom Queries is limited to your account, ensuring your data is not used to enhance general pretrained models.
- Convenience: Custom Queries provides a fully managed inference experience, saving you the overhead and expenses of training and operating custom models.
Conclusion: Evolve Your Company with AI
Custom Queries empowers you to leverage the power of AI to customize Amazon Textract for your business-specific documents. By automating document processing with higher accuracy, you can stay competitive and redefine your way of work.
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