With technologies advancing and the automated processes taking the center stage swiftly, the application of Artificial Intelligence (AI)-based document processing platforms has also increased substantially. As organizations are finding it difficult to manage structured and unstructured content, they have started to embrace digital transformation, especially in Artificial Intelligent document processing dominion.
Due to the rapidly increasing content, enterprises have begun to implement intelligent document processing that will not only automate the activity of capturing, extracting, and processing content from multiple domains but also it will require the least possible manual workforce. Out of the many technologies controlling business operations, AI-based Intelligent Document Processing (IDP) platforms stand out, primarily due to their ability to lessen the turnaround time and boost productivity. Therefore, AI-based document processing platforms have been receiving a lot of consideration lately for their ability to operate processes with maximum efficiency and minimum risks.
But, before getting deeper into document processing, it will be good to first get a grip over two concepts:
- What is Artificial Intelligence (AI)?
- What is Intelligent Document Processing (IDP)?
What is AI?
Artificial intelligence is the replication of human intelligence processes by robots, especially computer systems. It is a solution in which a machine mimics the cognitive actions that human mind relates with human minds such as problem solving, reasoning, social intelligence, natural language processing (NLP), knowledge representation and general intelligence.
What is IDP?
Intelligent Document Processing (IDP) is a set of solutions which automate document processing by utilizing artificial intelligence, machine learning and computer vision. IDP solutions use these tools to extract unstructured data from documents like PDFs, emails, and scanned documents, and transform it to structured data.
The data automation process helps users to understand the information included in the document, to extract, and process for further analysis. IDP captures, extracts, classifies, and exports information by applying AI technologies.
Best Five AI-based Document Processing Platforms
Xtracta
Xtracta provides automation software powered by AI for document processing. It offers its services to firms like Volvo, where eDocs are used to minimize time by 40% in invoice entry.
With the assistance of AI engine, which demands no manual templates unlike in traditional optical character recognition (OCR) techniques, Xtracta driven services process over 10 million pages per month.
This AI engine is a ‘set and forget’ engine because it self-learns the new document designs without the requirement of new templates.
Serimag
Serimag works correspondingly with the Barcelona Supercomputing Center (BSC) to categorize documents based on neural systems. Serimag is unique in the sense that its invention combines both text and graphics in an integrated manner within a document, of course without the requirement for parametric coupling modules.
An automatic classification and extraction system was established by Serimag to automate the administering of ‘customers supporting documentation’ and standardization benchmarks.
ABBYY FlexiCapture
FlexiCapture platform, one of the most sought-after platforms in the market, leverages machine learning to automatically organize, extract, authenticate and direct business-critical data.
Classification technology identifies every inbound document type, comprising images, by applying deep learning Convolutional Neural Networks (CNN) and demarcates documents by appearance or pattern; and text classification, which relies on statistical and semantic text analysis.
Parascript
Parascript offers computer vision solutions for text and image classification through AI techniques. It employs a topological style for character recognition using curve tracing fueled by neural networks. Parascript employs computer vision to accomplish tasks like OCR and handwriting recognition.
A few examples of computer vision solutions by Parascript comprise:
- Region of interest location on flats and parcels, and letters
- Automated location recognition on envelope images
- Check stock and signature verification
- Parascript utilizes convolutional neural systems for deep learning, Hidden Markov Models, Bayesian-based algorithms, and support vector machines.
Microblink
Microblink, an R&D company, creates computer vision technology optimized for real-time management on mobile devices. Improved neural networks and deep learning methods are applied to provide the most accurate text recognition locally on a mobile tool.
Features include:
- Real-time image processing
- Functions locally on-device, without an internet connection
- Efficiently supports paper and electronic payment slips in various standards and countries
Scope of AI-Based Document Processing Platforms
By combining Intelligent Document Processing (IDP) platforms with artificial intelligence, industries can reinstate ample rule-based, repetitive, programmed, and human operations. With the IDP and the automation industry growing exponentially recently, the usage of such platforms will lead to faster, extra-protected, and reliable core business services. The purpose is to boost efficacy and keep the costs grounded and maintain extreme security levels. These platforms can hugely enhance the proficiency of their processes, in all the repetitive and manually programmed processes.
Conclusion
The application of AI-Based document processing platforms has become compulsory with the content burgeoning and organizations facing a daunting task managing all of them manually. With the document processing platforms able to seamlessly integrate with the existing infrastructure and automate the document processing end-to-end, all the global industries are certain to thrive and prosper with the contemporary consumers eyeing for secure, quicker, and cost-effective solutions.