Key Features
AI-Powered Analysis
Uses advanced AI models to understand document content and extract structured information
Multimodal Support
Process text documents, images, and PDFs with the same AI-powered approach
Custom System Prompts
Configure specific instructions to extract exactly the information you need
Testing Interface
Test your system prompts and field extraction before deploying in automations
AI Provider Support
The Elementum Intelligence File Reader works with multimodal AI Services:Supported AI Providers
OpenAI Models
OpenAI Models
Best for: Advanced reasoning and complex document analysisSupported Models:
- o3 - Maximum intelligence for complex document analysis
- o4-mini - Fast processing for routine document tasks
- GPT-4 Omni - Balanced performance for general document processing
Google Gemini Models
Google Gemini Models
Best for: Cost-effective multimodal document processingSupported Models:
- Gemini 2.5 Pro - Advanced document analysis and large responses
- Gemini 2.5 - General-purpose document processing
- Gemini 1.5 Flash - Speed-optimized document analysis
To use Elementum Intelligence File Reader, you must first configure an AI Provider and create an AI Service. See AI Services for setup instructions.
Supported Document Types
The Elementum Intelligence File Reader can process various document formats:Text Documents
Text Documents
- PDF - Text-based and scanned PDFs
- DOC/DOCX - Microsoft Word documents
- TXT - Plain text files
- RTF - Rich text format
- HTML - Web pages and HTML documents
Image Documents
Image Documents
- JPG/JPEG - Compressed images with text
- PNG - Portable network graphics
- TIFF - Tagged image format
- BMP - Bitmap images
- GIF - Graphics interchange format
Complex Documents
Complex Documents
- Scanned documents - AI can read text from scanned pages
- Multi-page PDFs - Process entire documents or specific pages
- Mixed content - Documents with text, images, and tables
- Handwritten text - Basic handwriting recognition capabilities
Creating an Elementum Intelligence File Reader
1
2
Navigate to File Readers
In your application, go to File Readers section
3
Create New Reader
Click + File Reader and select Elementum Intelligence from the document type options
4
Configure Basic Settings
Name: Enter a descriptive name (e.g., “Contract Analysis AI”)Description: Optional description for your teamAI Service: Select your configured AI Service
5
Configure System Prompt
Write a custom system prompt that instructs the AI on what information to extractExample: “Extract the contract parties, effective date, termination date, and key obligations from this document.”
6
Define Output Fields
Configure the fields you want the AI to populate based on your system promptExample Fields: contract_parties, effective_date, termination_date, key_obligations
7
Test with Sample Documents
Upload test documents to validate that the AI extracts the correct information
System Prompt Configuration
Writing Effective System Prompts
The system prompt instructs the AI on how to analyze documents and what information to extract:- Basic Prompts
- Advanced Prompts
- Industry-Specific Prompts
Simple Extraction:Best for: Simple, straightforward document analysis
System Prompt Best Practices
Be Specific
Clearly define what information you want extracted and in what format
Provide Context
Explain the document type and purpose to help the AI understand context
Define Formats
Specify date formats, number formats, and text formatting requirements
Handle Edge Cases
Include instructions for handling missing information or unusual formats
Field Configuration
Configure output fields that match your system prompt requirements:Field Types and Configuration
Standard Field Types
Standard Field Types
Text Fields:
- Text - General text content
- Long Text - Extended text content
- Email - Email addresses with validation
- Phone - Phone numbers with formatting
- URL - Website addresses
- Date - Date values (YYYY-MM-DD)
- DateTime - Date and time values
- Time - Time values only
- Number - Integer values
- Decimal - Floating point numbers
- Currency - Monetary values
- Percentage - Percentage values
Advanced Field Types
Advanced Field Types
Structured Data:
- JSON - Complex structured data
- Array - Multiple values in a single field
- Boolean - True/false values
- Enum - Predefined options
- Required - Field must be populated
- Optional - Field can be empty
- Default Value - Value to use if not found
- Format Validation - Ensure data meets format requirements
Testing and Validation
Always test your Elementum Intelligence File Reader with representative documents before using in production automations. This ensures the AI extracts the correct information.
Testing Process
1
Upload Test Documents
Use actual business documents similar to those you’ll process in production
2
Review Extracted Data
Check that the AI correctly identifies and extracts the required information
3
Validate Field Accuracy
Ensure extracted data matches expected formats and values
4
Test Edge Cases
Try documents with missing information, unusual formats, or poor quality
5
Refine System Prompt
Adjust the system prompt based on test results to improve accuracy
Common Testing Scenarios
- Document Variations
- Content Variations
Test with:
- Different document layouts
- Various quality levels (scanned vs. digital)
- Multiple page lengths
- Different file formats
- Consistent field extraction
- Handling of poor quality documents
- Processing speed across formats
Using in Automations
Integration with Automation Workflows
The Elementum Intelligence File Reader integrates with automation workflows for sophisticated document processing:Common Automation Patterns
Contract Analysis
Contract Analysis
Trigger: Email Received (contract attachment)
File Reader: Extract contract terms, parties, dates
Actions:
- AI Classification to determine contract type
- Create Record with extracted contract data
- Start Approval Process for contract review
- Send Email Notification to legal team
Invoice Processing
Invoice Processing
Trigger: Attachment Added (invoice PDF)
File Reader: Extract vendor, amounts, line items
Actions:
- Search Records to find existing vendor
- Run Calculation to validate amounts
- Update Record Fields with invoice data
- Start Approval Process based on amount
Form Processing
Form Processing
Trigger: Document Upload (application form)
File Reader: Extract applicant information
Actions:
- Transform Data to standardize formats
- AI Classification to assess application quality
- Create Record for applicant
- Send Email Notification with next steps
Advanced Workflow Integration
Combine AI document analysis with other AI capabilities:- Document Upload: Complex research report
- Elementum Intelligence Reader: Extract key data points
- AI Summarization: Create executive summary
- AI Classification: Categorize findings
- Create Record: Generate comprehensive analysis
Best Practices
Prompt Engineering
Invest time in crafting precise system prompts for optimal extraction results
Document Quality
Use high-quality documents when possible to improve AI accuracy
Validation Testing
Test extensively with real documents before production deployment
Error Handling
Implement automation logic to handle extraction errors gracefully
System Prompt Optimization
Effective Techniques:- Use clear, specific language
- Provide examples of desired output
- Include formatting instructions
- Specify handling of edge cases
- Break complex tasks into smaller parts
- Overly complex prompts
- Ambiguous instructions
- Missing format specifications
- Unclear field definitions
- Insufficient testing
Advanced Features
Multi-Document Processing
Process multiple related documents in a single workflow:1
Document Batching
Configure automation to handle multiple document uploads
2
Contextual Analysis
Use AI to understand relationships between documents
3
Cross-Document Validation
Verify information consistency across documents
4
Comprehensive Reporting
Generate reports combining insights from all documents
Dynamic Field Extraction
Adapt field extraction based on document type:- Handles various document types with single reader
- Optimizes extraction for specific document formats
- Reduces configuration complexity
- Improves processing accuracy
Integration with AI Search
Combine document extraction with AI search capabilities:Document Indexing
Document Indexing
Extract and Index: Use extracted data for AI search indexing
Search Enhancement: Improve search results with structured data
Content Discovery: Find related documents using extracted information
Knowledge Management
Knowledge Management
Information Extraction: Extract key facts and insights
Knowledge Base: Build searchable knowledge repositories
Smart Retrieval: Use AI to find relevant information quickly
Error Handling and Troubleshooting
Common Issues
Poor Extraction Quality
Poor Extraction Quality
Symptoms: AI extracts incorrect or incomplete informationCauses:
- Unclear system prompt
- Poor document quality
- Inappropriate AI model selection
- Insufficient context in prompt
- Refine system prompt with more specific instructions
- Improve document quality before processing
- Try different AI models for better results
- Add more context and examples to prompts
Processing Failures
Processing Failures
Symptoms: File Reader fails to process documentsCauses:
- AI service unavailable
- Document format not supported
- File size too large
- Network connectivity issues
- Verify AI service configuration
- Check supported document formats
- Optimize document size
- Implement retry logic in automations
Inconsistent Results
Inconsistent Results
Symptoms: Same document types produce different extraction resultsCauses:
- Ambiguous system prompt
- Variable document quality
- Model temperature settings
- Insufficient training examples
- Make system prompts more specific
- Standardize document formats
- Adjust AI model parameters
- Provide more examples in prompts
Validation Strategies
Implement validation checks in your automations to ensure extracted data quality and handle edge cases.
- Required field validation
- Format validation (dates, numbers, emails)
- Range validation for numeric fields
- Pattern matching for structured data
- Cross-field validation for consistency
Performance Optimization
Processing Speed
Optimization Techniques:- Use appropriate AI models for task complexity
- Optimize document size and format
- Implement parallel processing for multiple documents
- Cache results for repeated processing
- Use faster models for simple extraction tasks
Cost Management
Cost Optimization:- Choose cost-effective AI models for routine tasks
- Optimize system prompts to reduce token usage
- Implement caching for repeated document types
- Use batch processing for multiple documents
- Monitor usage and adjust processing frequency
Integration Examples
Legal Document Processing
Medical Record Processing
Financial Document Analysis
Comparison with Other File Readers
When to Use Elementum Intelligence File Reader
Choose Elementum Intelligence when:- Processing complex, unstructured documents
- Need intelligent content understanding
- Working with various document formats
- Requiring custom field extraction logic
- Handling documents with mixed content types
- Processing simple text extraction (Text File Reader)
- Working with standard business forms (Purchase Orders Reader)
- Handling structured data files (Table File Reader)
- Processing JSON data (JSON File Reader)
Capability Comparison
Feature | Elementum Intelligence | Text File Reader | Purchase Orders Reader |
---|---|---|---|
Flexibility | ⭐⭐⭐⭐⭐ | ⭐⭐ | ⭐⭐⭐ |
Accuracy | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
Cost | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
Speed | ⭐⭐⭐ | ⭐⭐ | ⭐⭐⭐⭐ |
Complexity | ⭐⭐⭐⭐⭐ | ⭐⭐ | ⭐⭐⭐ |
Next Steps
AI Services
Configure AI providers and services to power your document processing
Automation System
Learn how to integrate AI document processing with automation workflows
OpenAI Setup
Set up OpenAI for advanced document analysis capabilities
Gemini Setup
Configure Google Gemini for cost-effective multimodal document processing
The Elementum Intelligence File Reader brings the power of AI to document processing, enabling sophisticated extraction and analysis of complex documents. Use it when you need intelligent understanding of document content beyond simple text extraction.