Many business processes still rely on handwritten information, such as field forms, approval notes, and document annotations. Traditional OCR struggles with this type of input. ChromeIS Handwritten Text Recognition is designed specifically to interpret natural handwriting, adapting to different writing styles, spacing, and alignment.
Handwritten Text Recognition focuses on how people actually write, rather than expecting uniform or perfectly shaped characters. The system examines stroke direction, spacing between letters, and surrounding context to interpret handwritten content accurately. This allows it to handle variations in writing style, pressure, and alignment across different documents. Because the process adapts dynamically instead of relying on rigid rules, handwritten data is captured with greater accuracy and fewer interruptions. This reduces the need for manual review and makes it possible to automate workflows that previously depended on time-consuming data entry.
