Invoice Data Extractor
Invoice Data Extractor is an AI-powered tool designed to convert invoice images into structured, machine-readable data. Developed using the BuildShip AI agent platform and powered by GPT-4 Vision, this solution intelligently parses visual content from diverse invoice formats and returns key information as a structured, stringified JSON object. Additionally, it dynamically generates a custom JSON schema tailored to each unique invoice structure.
Tool Name:DocumentExtarctor
Tool Trigger API-a17fbe75e76b54a052e31f3489e3e588cebd286889d47829877c7691e04e7d8b
Flow
Key Features
- Image-Based Input
Supports invoices in image formats (JPG, PNG) or scanned PDFs.
- Smart Field Extraction
Automatically identifies and extracts essential fields, including:
- Invoice number
- Dates (invoice, due)
- Vendor and recipient information
- Line items and total amount
- Tax and payment details
- Dynamic JSON Schema Generation
Creates a customized JSON schema based on the structure and content of each invoice, enabling flexibility across various invoice formats and layouts.
- Structured Output
Returns results as well-formatted, stringified JSON — ready for downstream automation and integration using JavaScript
- No Predefined Templates Required
Adapts to diverse invoice styles without needing prior schema definition or template configuration.
Technology Stack
- Large Language Model (LLM): GPT-4 Vision
- Agent Platform: BuildShip
- Input: Invoice image (JPG, PNG, JPEG)
- Output:
- Structured stringified JSON
- Custom JSON schema depend on innvoice
How It Works
- Upload
User uploads an invoice image through the interface or Tool Trigger API.
- Processing
GPT-4 Vision interprets the document’s visual layout and content.
- Schema Generation & Extraction
The system first generates a tailored JSON schema based on detected fields, and then populates it with corresponding values from the document.
- Output
The final output includes:
- A stringified JSON object containing the invoice data
- A JSON schema outlining the structure of the extracted fields
Sample Input
Sample Output
{ \"invoice_details\": { \"payment_for\": \"RISHIT RASTOGI\", \"division\": \"ME\", \"standard_course\": \"B Tech\", \"registration_code\": \"ME22B2017\", \"academic_year_start\": \"2023-04\", \"academic_year_end\": \"2027-03\", \"fee_description\": \"Jan-May 2025\", \"payment_date\": \"2024-12-30T10:03\", \"qfix_reference_number\": \"J9GCUHNK22B2017\", \"fee_amount\": 105140.00, \"late_payment_charges\": 0.00, \"other_charges\": 0.00, \"discount_amount\": 0.00, \"remaining_amount\": 0.00, \"paid_amount\": 105140.00, \"mode_of_payment\": \"DEBIT CARD\" }, \"itemized_charges\": [ { \"description\": \"TUITION FEE\", \"amount\": 66000.00, \"paid\": 66000.00 }, { \"description\": \"SEMESTER FEE\", \"amount\": 4800.00, \"paid\": 4800.00 }, { \"description\": \"HOSTEL FEES\", \"amount\": 34340.00"
}
Use Cases
- Automated invoice entry and reconciliation
- Financial and tax document processing
- Integration with ERP/CRM systems
- AI-powered document parsing for enterprise workflows
