Understanding Intelligent Document Recognition (IDR)

Paper trail and record-keeping represent an inevitable part of doing business, be it a large international corporation or a family-run local business. Scanning, sorting, tagging, and storing multiple invoices, bills, and so on encroach upon employees’ time and power. Manual processing of a docflow is slow and error-prone.  

This is where IDR solutions come to the forefront — smart automation of otherwise tedious document workflow saves precious time and high-value human resources for other, more creative and/or strategic tasks.  

IDR: What’s in a Box?

Intelligent Document Recognition, often addressed as IDR, is AI-geared software developed for automation and optimization of routine manual operations.  

IDR functionality comprises 3 primary capabilities:

• Classification of available documentation. The software can systematize industry-specific documentation of different types, both structured & unstructured. Sorting out documents by format or categories takes seconds instead of days or weeks.

•  Data retrieval. Once documents are classified, the software retrieves the necessary data.

•  Data export. Extracted information is exported and can be added to the existing databases for further processing.  

As a result, enterprises gain a competitive advantage due to shortened processing time, higher precision, elimination of errors, and overall higher ROI, apart from better use of human resources.

IDR: The Workflow Procedure

IDR utilizes OCR technology enriched with AI-based models and ML capabilities for scanning and classification of various types of documentation, extraction and further export of substantial data.

The IDR technology works as follows:

1.       The software identifies the documentation type via analysis of the structure and format.

2.       Once the type of a document is determined, OCR technology is deployed to transform a document into a digital file for further analysis.

3.       The relevant data is extracted from respective fields. The data retrieval mechanism utilizes an ML algorithm that can be trained to identify particular patterns that were not clearly labeled initially.

4.       Next, the extracted data is exported and added to the existing databases for the consequent indexing and analysis.

The key distinction between IDR and OCR processes is in IDR’s capability to deal with a broad range of unstructured (semi-structured) documents and self-learning capabilities. A built-in set of machine learning rules enables IDR to continuously extend and improve its capabilities and precision.

Advantages of Using IDR

Intelligent solutions enhance business performance and simplify routine operations. Regardless of niche, business owners note the following advantages of IDR:

• High precision. Automation of repetitive procedures helps companies to achieve unprecedented accuracy in managing the document workflow. Human errors can be avoided via automatic processing of huge volumes of documentation; the extracted data is accurate and ready for further use instantly.   

• Faster speed of docflow processing. Large data volumes are analyzed and processed almost instantly delivering relevant information in a ready-to-use format in a matter of seconds or minutes.

• Reduced costs. Dedicated software is capable of determining, extracting, and exporting information 300 times faster than human resources, while human power can be used more efficiently for decision-making based on analyzed and ready-to-use data. As a result, a company gains a competitive advantage thanks to the higher efficiency of customer service and sales.

• Optimized use of resources. Instead of carrying out repetitive operations, human specialists can dedicate their time to higher-value tasks.   

•  Full integration with the company's existing IT ecosystem. IDR solutions can be seamlessly integrated with various software solutions.

•  Elevated customer service. Implementation of IDR ensures more precise information and fast response rates that lead to higher client satisfaction and increased total efficiency.

IDR Applications

For many institutions and enterprises, IDR has become an indispensable tool that shortens time and reduces the effort needed to process and manage extended data volumes. Both standard and tailored IDR solutions have found a wide application in e-commerce, the healthcare sector, transportation and logistics, fintech, real estate, insurance, and many other industries. They are especially beneficial for enterprises dealing with multiple unstructured (and/or semi-structured) documents, particularly multi-language and handwritten documentation.  

For instance, processing of health records, bills, and invoices within the healthcare sector can refine the patient care notably through faster and more efficient information management. Forms, insurance claims, prescriptions, bills, treatment records - IDR can be pre-configured to meet the unique requirements of an organization.

Businesses operating in the logistics niche benefit greatly from paper flow automation in terms of improved customer support, streamlined bills and invoice tracking, and permit management. Elevated transparency, data precision and availability help to boost efficiency and eliminate hold-ups along the entire logistics chain. 

In the banking sector, multiple applications, invoices, and all sorts of forms speed up and enhance data management resulting in optimized goal-setting and strategic planning.

The efficiency of e-commerce is based primarily on meeting customer expectations and service quality. When the back-office routine paperwork is automated and all customer-related data, including orders, invoices, bills, and shipment tracking, is processed fast, the sales process is accelerated resulting in higher performance.   

In conclusion

Automated document recognition considerably enhances the output of companies with a heavy docflow. With custom-tailored Graip.AI IDR solutions that are tuned up specifically to answer industry-specific requirements; businesses and governmental institutions not only streamline the docflow and boost yielding capacity but also cut operational expenditures, increase returns on investments, get ahead of competitors and open new revenue vistas.