Automatically extracts text, handwriting, and data from scanned documents. It goes beyond simple optical character recognition (OCR) to understanding the structure and relationships within documents. Here are the key points about it:
Uses advanced OCR to accurately recognize and extract text from various document types.
Machine Learning (ML)
It employs deep learning models to understand document structure and context.
Natural Language Processing (NLP)
While not a primary focus, the system’s ability to understand document context involves some NLP techniques.
Automating data entry from forms
Captures and organizes data from structured and unstructured forms, reducing manual input and errors.
Creating searchable document archives
Converts scanned documents into searchable digital files, making information retrieval quick and efficient.
Analyzing legal and healthcare documents
Understands complex legal and medical texts, extracting critical information for compliance and decision-making.
Extracting information from financial documents
Identifies key financial details such as balances, transactions, and account numbers for accurate record-keeping.
Processing invoices and receipts
Automatically extracts relevant details like vendor names, amounts, and dates to streamline financial workflows.
Text extraction
Extracts printed text and handwriting from documents.
Table extraction
Recognizes and extracts data from tables, maintaining structure.
Query-based extraction
Allows users to ask specific questions about document content.
Form processing
Identifies and extracts key-value pairs from forms.
Layout analysis
Understands document layout, including headers, footers, and columns.
Accuracy
Provides highly accurate results, even for complex documents.
Integration
Easily integrates with other services for comprehensive document processing workflows.
Scalability
Can process large volumes of documents efficiently.
How it works
Users upload documents, whether scanned images, PDFs, or photos, to the platform. The system then processes these files using advanced machine learning models that go beyond traditional OCR by understanding document structure, layout, and context. This allows it to accurately extract text, handwriting, tables, and key data points while preserving relationships between elements.
Once processed, the extracted information is returned in a structured format—such as JSON, CSV, or directly integrated into enterprise systems—making it easy for further analysis, automation, or reporting.
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