Artificial Intelligence (AI) powers Intelligent Document Processing (IDP) by the implementation of automation & Machine Learning (ML) pathways. These are particularly useful for written applications, including driving accurate, efficient, scalable & secure data extraction for meaningful results. Moreover, these analytical & predictive insights can be actionable through statistical extrapolation. So, let us delve into the ever-evolving world of Intelligent Document Processing software solutions.
What are Intelligent document processing software solutions?
IDP tools are robust solutions to ensure resource efficiency by focusing on data management, its handling & hygiene too. So, what is intelligent document processing, then? IDP is a culmination of digital technologies (including AI & ML) and deep learning with Natural Language Processing (NLP). Intelligent document processing solutions rely upon these underlying principles to process documents & extract required or pertinent information.
AI-powered Intelligent Document Processing software is the answer to many organizational woes in implementing AI & IDP within a connected environment. This drives efficient frameworks, ensuring continuity of information at all levels. In addition, multilevel navigability promotes ergonomic data management & accessibility.
How does intelligent document processing operate?
Intelligent document processing utilizes intelligent document technology solutions to classify documents, then process the required data with pattern recognition technology. Following the processing of these documents, intelligent document processing software extracts the important data and assembles them into an accessible format.
Difference between intelligent document processing and automated document processing
Some assume that IDP and automated document processing are the same. However, there is a slight difference in the documents they act upon. Automated document processing is applied mostly for digitizing paper documents while intelligent document processing fully processes many distinct types of documents and consolidates their relevant data, thus nullifying the requirement for human data processors.
How do I implement intelligent document processing software?
Employing intelligent document software solutions starts with the assessment of document processing workflows to identify the ones that can be automated. Once the documents that need to be automated are identified, then it becomes mandatory for companies to find out the workflows that need the ultimate level of accuracy to initiate the automation process accordingly.
Intelligent document processing use cases
Just before exploring this, let us have a brief overview of the entire IDP process:
Input > Priming (pre-processing) > Detection cum data segmentation (classification) > Extraction (via OCR, deep ML & NLP) > Post processing (RPA, commercial logic & ERP integration)
Now, these are some popular applications of IDP:
- Banking, credit, finance & insurance: whether it is loan application processing, customer satisfaction, claims, data management, document security, KYC, mortgaging, or account opening, IDP caters for all – in terms of extraction & processing, as well as analysis.
- Healthcare: be it admission documents, clerical services, patient data handling, record management, health monitoring, medication information & clinical history
- Transport & logistics: supply chain forms, inventory management, demand sensing, invoice & contract verification, ERP integration, data validation plus delivery confirmation
- Legal: ranging from insurance claims eligibility to contractual authentication or even underwriting processes themselves, IDP serves to analyze, scrutinize & verify documentation
- RPA & robotic intelligence integration for enterprises, propelling automation with data points extracted from information volumes. This drives interconnectivity & efficiency.
Following this flow:
Absorb & Extract intricate document orientation, written & visual items.
Hone extracted data with detailed context.
Extract actionable data insights.
Use analyzed information through downstream integration & query.
What does the future hold for IDP?
In addition to addressing automating & streamlining existing conventions for documentation, IDP will bring a host of other evolving advantages. Its holistic approach drives many industries beyond their current capabilities. For instance, the ability to search for specific keywords or terms via a phrase query search (by applying intelligent filters) is one such application. This can be extended beyond the existing realms of the education, financial, retail & leisure industries with integrated solutions. These could include the ability to revise a current contract, update or even overhaul a press release – the possibilities are endless.
What is intriguing about IDP is its ability to learn continually deep, process, redefine & analyze information efficiently. Moreover, driving new processes with streamlining in mind can further enhance efficiency: predictive pipelines, deep learning, flexible information management & data handling.
Edge Verve’s XtractEdge platform does just that by offering the following salient features:
- Integrated ERP connectors
- Automated document categorization as per written text content or visual orientation
- Detailed & specific multiformat document data extraction, which is template training agnostic
- Object detection via Deep Learning Computer Vision & NLP models to extract intent & entity
- Cognitive Search queries for NLP & keywords
- Intuitive GUI orchestration Workbench guides manual review with a feedback loop with personalized & flexible post-processing workflows
- Performance analytics dashboard drives stellar Quality Control
IDP will always dominate the business automation industry with its AI, ML & NLP capabilities – all unified in one package. This underpins the principle of data intelligence, autonomy, security & scalability. The day that most organizations (if not all) realize & can implement IDP, the better equipped our industries will become to deal with data volumes at scale. This is irrespective of the infrastructure available (bar interconnected server networks & computing hardware), industry & document type.
The quicker we can achieve a more extensive adoption of this data enablement, the greater our global ability to identify & exchange data at speed will become. This is imperative for the upcoming web3 interface, where information will become ever more decentralized theoretically. It is only feasible to operate in such environments with interconnected pathways. Thankfully, IDP’s integration abilities live up to this necessary expectation.
One of the best features of IDP is that it can adapt itself to diverse domains across industries. Hence, it is fair to acknowledge that IDP analyze virtually any document type at a much higher speed & scale. The only hindering factor is organizational adoption & active deployment of such tools. With these in order, it is only a matter of time before we witness a revolution in how we input, view & retrieve almost any kind of information. The future is mysteriously approaching fast: are you ready to embrace this massive change?