Updated in FlowX.AI 5.5.0The “Extract Text from Document” node has been renamed to Extract Data from File and now supports image inputs, configurable extraction strategies, image extraction options, and signature detection.
Overview
The Extract Data from File node extracts text and structured data from documents and images within Agent Builder workflows. It supports multiple extraction strategies so you can balance accuracy, speed, and cost based on your document types.Supported file formats
| Category | Formats |
|---|---|
| Documents | PDF, DOCX, XLSX, XLS, XLSM, PPTX |
| Images | JPG, PNG, TIFF |
Image files are automatically converted to PDF before processing. This conversion is handled by the Document Parser service.
Configuration
To add the node to an Agent Builder workflow:- Open your workflow in Agent Builder
- Add an Extract Data from File node from the Document Operations category
- Configure the extraction settings described below
Response key
The key where the extraction results are stored in the workflow data.Example:
extractedDataContent extraction strategy
Select the method used to extract content from the file. Each strategy has different accuracy, speed, and cost characteristics.
| Strategy | Best for | Speed | Cost | Accuracy |
|---|---|---|---|---|
| LLM Model | Complex layouts, handwritten text, mixed content | Slow | High | High |
| OCR Engine | Scanned documents, image-heavy files | Medium | Medium | Medium |
| Text Parsing | Clean digital PDFs with selectable text | Fast | Free | Low–Medium |
- LLM Model
- OCR Engine
- Text Parsing
Uses AI vision models (such as GPT-4o) to analyze document content. This strategy provides the highest accuracy and can handle:
- Complex page layouts with multiple columns
- Handwritten text and annotations
- Mixed content (text, tables, images on the same page)
- Documents with non-standard formatting
Image extraction options
When using LLM Model or OCR Engine, you can configure how images found within the document are handled.Select how images embedded in the document should be processed.
| Option | Description | When to use |
|---|---|---|
| Image Description | Generates a text description of images | When you need to understand what images depict (charts, photos, diagrams) |
| Image Content | Extracts text and data from images | When images contain text, tables, or data you need to capture |
LLM Model supports both Image Description and Image Content. OCR Engine supports only Image Content.
Image extraction options are not available when using the Text Parsing strategy, since Text Parsing only handles selectable text content.
Signature detection
Enable detection of signatures within the document.Default: OFFWhen enabled, the node identifies areas of the document that contain signatures and includes their locations in the extraction results.
Signature detection is only available when using LLM Model or OCR Engine strategies. It is not available for Text Parsing.
Examples
Processing a scanned invoice
Processing a scanned invoice
Scenario: Extract line items and totals from a scanned paper invoice.Configuration:
- Extraction Strategy: OCR Engine
- Image Extraction: Image Content
- Detect Signatures: ON (to capture the approval signature)
Analyzing a contract with charts
Analyzing a contract with charts
Scenario: Extract text and understand visual elements from a contract that includes charts and diagrams.Configuration:
- Extraction Strategy: LLM Model
- Image Extraction: Image Description
- Detect Signatures: OFF
Extracting text from a clean PDF
Extracting text from a clean PDF
Scenario: Extract text from a digitally generated report PDF.Configuration:
- Extraction Strategy: Text Parsing
- Image Extraction: N/A (not available for Text Parsing)
- Detect Signatures: N/A (not available for Text Parsing)
Best practices
Start with Text Parsing
For digital PDFs, try Text Parsing first. Only use OCR or LLM if the results are insufficient.
Match strategy to document type
Use OCR for scanned documents, LLM for complex layouts, and Text Parsing for clean digital files.
Consider cost at scale
LLM processing costs increase linearly with page count. For high-volume workloads, use Text Parsing or OCR where possible.
Turn off unused features
Turn off signature detection and image extraction when not needed to reduce processing time and cost.