AI-powered data extraction
Intelligent document processing combining LLMs, machine learning, and 15+ years of extraction innovation. Automatically extract key-value pairs, tables, forms, and structured data from PDFs and images. No training data or manual templates required. A hybrid AI approach delivers higher accuracy than pure ML solutions.
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Combines LLMs, machine learning, heuristics, and mathematics to deliver higher accuracy than pure AI or ML solutions, backed by more than 15 years of continuous innovation.
Automatically detect and extract phone numbers, IBANs, credit cards, names, emails, and custom fields from unstructured documents.
Extract structured data from financial reports, invoices, bank statements, forms, and surveys with adaptive layout understanding.
Automatically classify invoices, contracts, receipts, and resumes using natural language instructions. No manual labeling required.
AI-powered extraction of structured fields from unstructured documents.
Extract tables from financial reports, invoices, and bank statements.
Extract form field values and checkbox selections from surveys.
Extract machine-readable zones from passports, IDs, and checks.
Specialized extraction for invoices and bank statements.
LLM-powered classification and intelligent extraction.
Extract data from PDFs, images, Office documents, emails, and 100+ file formats with a unified API that provides automatic format detection and preprocessing.
Phone numbers IBANs Credit cards Names Emails Tables Forms Invoices Bank statements MRZ MICR OMR Barcodes Natural language Classification Custom templates INTELLIGENT DOCUMENT PROCESSING
Combine LLMs with machine learning for intelligent document classification and structured data extraction. Process invoices, resumes, contracts, and forms with natural language instructions.
Classify invoices, contracts, receipts, and resumes without manual labeling or training data.
Extract fields using plain English instructions. No rigid templates or extensive coding required.
11 built-in validators for IBANs, credit cards, emails, phone numbers, VAT IDs, and addresses.
Process thousands of documents with multithreaded extraction for high-volume workflows.
The SDK uses a hybrid approach, combining LLMs, machine learning, heuristics, and mathematics to understand document structure and extract key-value pairs automatically. It analyzes spatial relationships, text patterns, and semantic meaning to identify fields like phone numbers, IBANs, credit cards, and custom data types. No predefined templates or manual configuration required. The system adapts to different document layouts and formats automatically.
Accuracy varies by document complexity, but the hybrid AI approach typically achieves 90–95%+ accuracy for structured fields like key-value pairs and tables. The system provides confidence scores for each extraction, allowing you to filter results by quality threshold. More than 15 years of continuous ML improvements and the combination of LLMs with traditional extraction methods deliver higher accuracy than pure AI/ML solutions, especially for complex or inconsistent document layouts.
Yes. The SDK includes specialized extraction for invoices, receipts, and bank statements. Extract vendor information, dates, amounts, line items, and custom fields using natural language instructions or built-in templates. The AI Document Processing module automatically classifies document types and extracts relevant fields without manual configuration. It works with invoices from any vendor or format, handling variations in layout and structure automatically.
The table extraction engine automatically detects and extracts tables from PDFs and images, handling complex layouts with merged cells, row/column spans, and nested tables. Export extracted tables to JSON, CSV, or structured formats. The system uses adaptive layout understanding to recognize table boundaries and cell relationships, even in documents with inconsistent formatting or poor scan quality. Works on both native PDFs and scanned documents with OCR.
MRZ (machine readable zone) extraction reads encoded data from passports, ID cards, visas, and driver’s licenses. MICR (magnetic ink character recognition) extracts routing and account numbers from bank checks. Both technologies provide automatic validation and parsing of extracted data. MRZ extraction supports all standard document types and formats, making it ideal for identity verification, border control, and KYC workflows. MICR extraction handles check processing and payment automation.
OMR (optical mark recognition) detects filled checkboxes and bubbles in scanned forms, surveys, questionnaires, and multiple choice tests. Create custom templates for your specific forms or use automatic detection. The system handles handwritten marks, checkmarks, and filled circles, with tolerance for scan quality variations. Ideal for processing surveys, exam papers, ballot forms, and any document with checkboxes or bubbles. Export results to structured JSON for analysis.
Yes. The AI Document Processing module uses LLMs combined with machine learning to automatically classify documents into categories like invoices, contracts, receipts, resumes, and custom types. No manual labeling or training data is required. Provide natural language instructions like “classify invoices, contracts, and receipts,” and the system will intelligently identify and sort documents based on content and structure. Works with 100+ file formats, including PDFs, images, and Office documents.
The system automatically recognizes phone numbers, email addresses, IBANs, credit card numbers, postal codes, dates, monetary amounts, VAT IDs, and many other structured data types. You can also define custom data types using patterns or natural language descriptions. The SDK includes 11 built-in validators for common field types, ensuring extracted data meets format requirements. Confidence scores help you assess extraction quality and filter results by reliability threshold.
Yes. All extraction methods work on both native PDFs and scanned documents. The SDK includes integrated OCR that automatically converts scanned images to searchable text before extraction. It supports 100+ languages and handles poor scan quality, skewed images, and low resolution. The extraction engine uses adaptive layout understanding to recognize structure in both machine-generated and scanned documents, making it suitable for processing legacy documents and physical forms.
Yes. The AI Document Processing module enables extraction using plain English instructions like “extract customer name, invoice date, and total amount.” There’s no need to define rigid templates or complex rules. The LLM-powered system understands context and can adapt to different document formats automatically. This approach works particularly well for semi-structured documents where field positions vary. Combine natural language instructions with built-in templates for best accuracy.
Extraction performance depends on document complexity and extraction type, but typical operations complete in seconds. The SDK supports multithreaded processing for batch operations, enabling you to extract data from multiple documents in parallel. For high-volume scenarios, distribute workload across multiple servers. Memory usage is optimized for large document sets, and you can process thousands of files efficiently with proper batch sizing and parallel processing configuration.