AI in document processing
In the business world, where there is a constant need to work with a large number of documents,
effective processing of these materials is crucial for achieving success. The traditional approach to document processing, which involves manual entry and review, is a time-consuming process prone to errors.
Just as it has transformed many other aspects of business, artificial intelligence (AI) brings significant changes to document processing, enabling faster and more precise handling of documents. AI tools, such as ownvia, automate routine tasks, reducing costs and the risk of errors while significantly increasing productivity.
This blog will introduce you to the world of Intelligent Document Processing (IDP), present the technologies used by IDP and showcase various applications of artificial intelligence in document processing.
Intelligent Document Processing can understand the context and meaning of informations.
WHAT IS AI DOCUMENT PROCESSING?
Document processing using artificial intelligence is referred to as Intelligent Document Processing
(IDP). IDP is an advanced process that enables the automatic classification and extraction of data from business documents using technologies such as artificial intelligence (AI), machine learning (ML), and optical character recognition (OCR).
Traditional OCR converts images into machine-readable text, while IDP can further classify document types, extract specific data, and understand the context and meaning of informations.
IDP has the capability to process all types of documents, regardless of their level of structure, making it an optimal solution for various industries.
While IDP focuses on document processing, Unstructured Data Processing (UDP) solutions take it a step further, enabling the analysis of any type of unstructured data, such as images, videos and audio.
These solutions allow organizations to extract valuable insights from a wide range of informations, enhancing decision-making and optimizing operations.
The combination of AI technologies such as OCR, NLP, machine learning, and computer vision transforms the way organizations manage documents and data.
TECHNOLOGIES IN DOCUMENT PROCESSING
Intelligent Document Processing (IDP) utilizes a combination of multiple technologies to optimize the data analysis and management process.
- Optical Character Recognition (OCR) is a technology that allows for the conversion of various types of documents, such as scanned papers, PDF files, or images, into machine-readable text formats. OCR works by analyzing the shapes of characters in an image, recognizing them and converting them into textual data that can be edited and searched, thus opening the possibility for further processing and analysis.
- Natural Language Processing (NLP) enables computers to understand, interpret, and generate human language. In intelligent document processing, NLP plays a key role in information extraction, document classification and context understanding, allowing for more precise and effective data management.
- Machine Learning (ML) is responsible for the automatic recognition and document classification. Machine learning models continuously learn from large amounts of dana how to extract information, recognize patterns, and optimize automation processes.
- Computer Vision (CV) handles visual data within documents, interpreting logos, signatures, watermarks, and images. It uses algorithms to extract visual elements and classify documents. Furthermore, it optimizes label recognition or optical character recognition, further enhancing the overall understanding of the document’s content.
HOW DOES IDP WORK?
Intelligent Document Processing (IDP) begins with the input and uploading of files. This is followed by the pre-processing of documents, which includes steps such as binarization, stain removal and distortion, and image rotation to ensure that the document is optimal for further processing.
The IDP system uses technologies like NLP and OCR for intelligent document classification, automatically recognizing the type and content and directing them to the appropriate processes. Next is the data extraction phase, which utilizes advanced AI technologies, such as machine and deep learning, to extract key information such as names, dates, and amounts. Following this is validation, where the accuracy and relevance of the data are checked, and potential errors are flagged for human review.
Through the human-in-the-loop (HITL) process, humans monitor the accuracy of processing, helping AI models learn from mistakes and become more precise. Finally, the data is integrated with existing business systems, allowing for further analysis and reporting.
AI tools for document processing significantly increase the speed, accuracy and efficiency of business processes.
ADVANTAGES OF USING AI TOOLS FOR DOCUMENT PROCESSING
Using AI tools for document processing brings numerous significant advantages that enhance business processes and increase operational efficiency.
- Automation and Efficiency:
AI tools for document processing automate everyday tasks such as data entry and validation, significantly reducing the need for manual labor. This speeds up business processes, enabling faster document processing and reducing costs associated with manual operations. - Accuracy and Reduction of Errors:
The use of AI technologies reduces the risk of human errors, especially in data entry and processing. More accurate data means fewer mistakes and more reliable decisions, thereby reducing costly oversights in business. - Cost and Resource Reduction:
Automated document processing allows for savings in time and financial resources, as it eliminates the need for manual labor with large volumes of data. Companies can reduce the number of qualified employees needed for these tasks while maintaining a high level of productivity. - Increased Productivity:
AI tools can process large volumes of documents simultaneously, allowing companies to manage business processes faster and more efficiently. Moreover, employees are freed from tedious tasks and can focus on strategically important jobs. - Scalability and Flexibility:
IDP solutions are scalable and can be adapted to changes in business, regardless of the size or type of task. This flexibility allows for easy adjustment to various business processes and industries.
EXAMPLES OF IDP APPLICATIONS
We will introduce you to several AI tools from the ownvia application through examples of using IDP.
- Digitization: IDP tools can convert paper documents into machine-readable formats such as PDF or Word, enabling easier text processing and searchability. The HandwriteConvert tool from the ownvia app allows for the digitization of handwritten notes, converting them into easily editable and searchable text.
- Intelligent Data Search: Using intelligent data processing, we can accurately search for specific data without manual document review. For example, using the ProductFinder tool, we can search all product names within texts or files and automatically generate an accurate list in just a few seconds. If we want to find various information related to a specific file, we simply upload it to the Chatbot / Data Analyst tool. We can then ask questions to the chatbot and quickly receive relevant information of interest.
- Categorization and Organization of Documents: IDP can classify documents by various criteria. This capability is extremely useful because organized documents allow for easy searching of specific information, resulting in more effective document management. Tools like the TextDomainAnalyzer can analyze text and accurately determine to which area it belongs.
- Automation of Document and Report Creation: With IDP, you can automatically fill in templates, generate detailed reports and complex legal documents, as well as create summaries. The ownvia Micro-App TermExtract allows for the extraction of relevant terminology candidates from texts. These candidates are translated into other languages, ensuring consistent use of specialized terminology in both the source and target languages. Additionally, the extracted terminology lists can be used to train neural machine translation (NMT) engines, improving translation quality and supporting the consistent use of terminology. This micro-app is particularly useful in technical documentation, where precise and consistent terminology is essential.
APPLICATION OF INTELLIGENT DOCUMENT PROCESSING IN VARIOUS INDUSTRIES
Artificial intelligence plays a key role in document processing across various industries, bringing significant benefits. In the legal industry, AI is used to analyze legal documents, contracts, and regulations, thereby increasing efficiency and accuracy. The financial industry utilizes AI for automating processes such as invoice processing, reporting, and credit requests, enabling faster and more accurate tracking of financial data. In the healthcare sector, AI improves the management of medical documentation and ensures the accuracy of patient data. In logistics, AI enables automatic recognition of shipping documents and invoices, speeding up supply chain operations. Human resources use AI for managing resumes and job applications, while governments apply AI to extract data from legal documents and organize public records.
All these applications contribute to more efficient operations and cost reduction across various sectors.
Artificial intelligence undeniably transforms the way companies process documents, enabling them to achieve greater efficiency, accuracy and significant cost savings. Given that the use of AI tools for document processing significantly optimizes document management, there is no doubt that AI tools will become even more popular and have more applications in the future. For companies that want to remain competitive, using AI technologies is no longer an option, but a necessity.
If you are ready to improve your document processing, register in ownvia and discover how our AI tools can revolutionize your business processes. ownvia can quickly tailor solutions that perfectly meet your specific needs.
Sign up today and step into the future of automated document processing!
