We all understand the value of artificial intelligence and how it is integral to any business in any vertical for them to have an in-depth understanding of their DMS. Intelligent Document Processing (IDP) goes a step further where it uses artificial-intelligence-based technologies to process structured, semi-structured, and unstructured documents. Although some businesses might not feel the need for AI, there are a number of businesses that include Intelligent Document Processing as an integral part of their hyper automation strategy, says Rene Brunt, Founder and CEO of Ubunye Holdings.
Intelligent Document Management leverages artificial intelligence (AI) and machine learning (ML) to identify documents, product development artefacts, and quality events impacted by a change and that is where the magic lies, having the insights and knowledge to enhance your customer journey.
AI is hugely beneficial to any business, it allows for automation, smart decision making, enhanced customer experience, manage repetitive tasks and it is critical for business continuity.”
— Rene Brunt, Founder and CEO of Ubunye Holdings
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Through ScannerVision, our Document Processing Solution, we have always been able to automate document workflows that operate seamlessly with scanned documents and various documents generated by other applications. This has been achieved through the creation of custom templates, which in turn enable straight-through processing of documents by automatically extracting metadata and storing the documents and metadata in various locations.
However, as with every Document Processing Solution, we needed to evolve, and our next logical step was the introduction of artificial intelligence with the Ubunye AI.
What is the Ubunye AI?
- Features & Benefits
Seamless Integration using the AI Connector
The Ubunye AI provides the ability for additional and in-depth document processing which is enabled by our AI module.
The Ubunye AI connector provides seamless integration of ScannerVision and the Ubunye AI and facilitates the transfer of documents and OCR results. - Quick Custom Template Configuration
Custom templates and workflows can be quickly designed in the Ubunye AI module for a customized solution. - Document models and learning capability
As the name suggests, the Ubunye AI module makes use of artificial intelligence to learn how to extract key data not only from common document types such as Invoices, Receipts, Business Cards, Identity Documents, and Vaccination Cards but also from any document types through model training. - Continuous Improvement With a continuous human feedback loop, you can improve the accuracy of your AI models to achieve higher confidence scores of the extracted data.
- Only pay for the pages you wish to cover. You only pay for the pages you send to the Ubunye AI so with effective template design you can keep costs low.
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Despite the drive and energy many organizations spent on digital transformation, many of them still spend quite a bit of time manually processing information from various forms of documents. Because of the nature of digital files such as PDFs, images, spreadsheets and even multimedia such as video, various facts and figures have to be processed and entered by hand. As a result, extracting relevant information remains problematic.
To improve the effectiveness and efficiency, AI is able to understand the semantics of content and automatically acquire knowledge. Through intelligent document processing (IDP), the process of data extraction automation from unstructured and semi-structured documents and conversion into structured and usable data. AI is the ability to extract, validate and file data with high accuracy and can therefore enhance and improve different business practices.
Because organizations collect data from diverse sources, the amount of unstructured data in their storage silos grows, ultimately hurting efficiency and costing money. AI can mitigate these troubles by identifying similarities between data through classification and extraction based on predefined criteria.
Machine learning can extract relevant information based on intent and meaning, and as such, properly address changes and variants in documents. These capabilities offer greater flexibility and scalability in document processing with minimal manual intervention.
Specialized machine learning algorithms analyze documents that contain rich components such as graphs and charts, then extract data and display document information. This includes everything from addresses and phone numbers to invoice amounts and employee and customer profiles.
Document management is critical for the distribution and preservation of knowledge, and AI has become a critical source of value creation that can be leveraged in every department.
There are 4 types of artificial intelligence:
Reactive machines:
The most basic types of AI systems are purely reactive, and have the ability neither to form memories nor to use past experiences to inform current decisions.
Limited memory:
This Type II class contains machines that can look into the past.
Theory of mind:
In psychology, this is called “theory of mind” understanding that people, creatures and objects in the world can have thoughts and emotions that affect their own behavior.
Self-awareness
The final step of AI development is to build systems that can form representations about themselves. Ultimately, AI researchers will have to not only understand consciousness, but build machines that have it.