The engine is designed to handle a wide range of documents, including scanned images, PDFs, and digital-born files. It effectively processes documents with varying image qualities, skewed pages, and those containing bordered, semi-bordered, or borderless tables.

Utilizing advanced machine vision and artificial intelligence technologies, the engine employs a layout understanding approach. This method combines layout analysis, OCR, key-value pair extraction, natural language processing, and named-entity recognition to accurately detect and extract tables without relying on predefined training models.

Yes, the GdPicture.NET Table Extraction engine provides functionalities to export detected tables directly to Excel spreadsheets (XLSX). This feature preserves the original document’s style, including text and cell colors, font sizes, and types, facilitating seamless data transfer for further analysis or reporting.

Yes. The engine can identify and extract multiple tables from a single document, even if they span across multiple pages. This capability ensures comprehensive data extraction from complex documents containing numerous tables.

The engine is versatile and applicable across various industries. Common use cases include:

• Invoice Automation: Extracting itemized billing information for streamlined accounting processes.
• Quality Control: Extracting data from inspection reports to ensure compliance with industry standards.
• Form Automation: Extracting data from structured forms for efficient data entry and processing.
• Data Reconciliation: Extracting financial data from statements for accurate record-keeping and auditing.

These applications demonstrate the engine’s ability to enhance efficiency and accuracy in document processing tasks.