Introducing a hybrid approach to using Document AI and GenAI
OCR / ICR
Supercharge AI automation with the power of reliable, accurate OCR

Boost AI efficiency with trusted OCR
Revolutionize how you work with documents using optical character recognition (OCR) and intelligent character recognition (ICR), the cutting-edge technology for image-to-text conversion, document recognition and processing.
Highly optimized to deliver unmatched efficiency, accuracy, and versatility, ABBYY’s OCR and ICR technologies adapt seamlessly to diverse needs, optimizing performance across various applications. Whether you're looking to extract data from complex forms, build the next-gen AI-powered app, or streamline enterprise workflows, our Document AI platform delivers consistent and high-quality results with purpose-built AI.
From static documents to dynamic AI-driven solutions
OCR technology converts scanned or handwritten documents into machine-readable, AI-ready text, maintaining the document's logical structure and original content. The extracted data becomes highly versatile, ready to power a wide range of AI-driven tools and processes.
OCR’s output transforms static documents into actionable, structured information, forming a critical bridge between raw data and intelligent automation, while opening new opportunities for efficiency and innovation across industries.
Where OCR meets AI innovation
- Within intelligent document processing (IDP), this structured data enables precise automation of tasks such as invoice processing, contract validation, or compliance checks.
- Combined with retrieval-augmented generation (RAG), the data enhances the ability to retrieve contextually relevant information for generating accurate responses.
- Autonomous agents, such as chatbots or virtual assistants, also benefit from this enriched data, allowing them to interact more intelligently using reliable document-based knowledge.
- Furthermore, the AI-ready output can fuel the training of advanced language models, increasing the quality and diversity of training datasets without manual preprocessing.
What is OCR?
Optical character recognition (OCR) is a technology designed to convert different types of documents, such as scanned paper documents, PDFs, or images, into editable and searchable data. By utilizing sophisticated algorithms and machine learning, ABBYY’s OCR identifies and processes machine printed characters, understands document layout and logical structure, and converts them into structured, machine-readable, AI-ready text. This allows organizations to digitize large volumes of paper-based information accurately and efficiently.
Precise OCR is a critical component of intelligent document processing, ensuring accurate data extraction and reliable outputs that drive business efficiency. Inaccurate data extraction can lead to misinformation, hinder decision-making, and compromise business operations, resulting in increased manual labor, higher costs, and reduced productivity. By unlocking content and insights trapped in documents, precise OCR enables seamless automation and supports smarter decision-making processes. It serves as the backbone of AI-based automation workflows, transforming unstructured data into actionable information for advanced technological solutions.
What is ICR?
Intelligent character recognition (ICR) is an advanced extension of optical character recognition (OCR) technology. While OCR is primarily designed to recognize printed or typed text, ICR specializes in processing handwritten characters with a higher degree of accuracy. This cutting-edge technology leverages artificial intelligence and neural networks to continuously learn and improve its recognition capabilities over time. ICR is particularly valuable in scenarios that involve handwriting-heavy documentation, such as forms, checks, or historical archives. By integrating ICR into document processing systems, organizations can further enhance the automation and digitization of complex workflows, minimizing manual data entry errors and streamlining information management.




















