In this information age in which we find ourselves, the acquisition of competitive advantages that allow optimizing the management and customer service becomes an essential task and a real challenge in the operational heart of any organization. Therefore, the implementation of technologies that favor the achievement of this objective in an automated manner becomes a necessary means to meet this challenge, and it is for this reason that intelligent document processing and RPA provide an indispensable resource that is gaining more and more followers.
Intelligent Document Processing or IDP is a technique used to extract information and data from text documents such as contracts, invoices, forms and other business documents. This technique is often used to automate the process of collecting and analyzing document data, which can save time and effort and improve data accuracy.
There are several tools and technologies that can be used for intelligent document processing, such as optical character recognition (OCR), natural language analysis algorithms and cloud-based document processing platforms. These tools are used to extract information from text documents accurately and quickly and to analyze document content in an automated manner.
Intelligent document processing can also be used in conjunction with artificial intelligence and machine learning to further improve the accuracy and speed of the data extraction process. For example, machine learning algorithms can be used to analyze large sets of documents and detect patterns and trends in the extracted data.
But let's start at the beginning, because we could not talk about intelligent document processing without first explaining how this information is processed?. Or rather, how does intelligent document processing work?
What is Intelligent Data Processing?
Intelligent data processing, also known as advanced data processing or real-time data processing, is a technique used to analyze large amounts of data quickly and accurately. This technique is often used in business and research applications, such as real-time decision making, pattern detection and predicting future results.
There are many different tools and technologies that can be used for intelligent data processing, such as distributed database systems, cloud processing platforms, and specialized programming languages. These tools are used to store, process and analyze large data sets efficiently and quickly.
Benefits of intelligent document processing:
Intelligent document processing offers several benefits, including:
- Time and effort savings: Intelligent document processing automates the process of collecting and analyzing document data, which means there is no need to spend time and effort manually reviewing each document.
- Increased data accuracy: by using IDP tools, human errors are less likely to occur when collecting and analyzing data.
- Increased efficiency in decision making: enabling companies to collect and analyze large amounts of data quickly and accurately, which can help improve decision making.
- Greater flexibility: because it can be used to process a wide variety of documents of different formats and content types.
- Increased scalability: by enabling companies to process large amounts of documents quickly and efficiently, which can be especially useful for companies that have to process large amounts of documents on a regular basis.
What about combining intelligent document processing with RPA?
When we combine intelligent document processing with RPA there are multiple direct benefits, such as:
- Faster data processing
- Cost reduction
- Standardization and operational speed
- Integration flexibility
- Ability to apply customized logics
IDP examples and use cases:
Invoice Processing: In order to avoid delays during the processing of receipt and payment of invoices between customer and supplier, the IDP allows to speed up the creation and document management of this procedure in a more agile way.
Fraud detection: IDP can help in the authentication and identification of risks associated with possible threats to customer data protection.
Medical records: processing forms, documentation or insurance claims during the administrative or operational management of healthcare personnel in an automated way thanks to AI, Machine Learning or natural language processing technologies will allow exponentially speeding up patient response times.
Customer records: Document automation will save countless hours of creating customer profiles and avoid human error associated with each process by improving the operational efficiency of all staff during that procedure.
Do you know Microsoft's solutions for intelligent document processing?
Microsoft has different IDP solutions to meet business or operational needs, for example:
- Microsoft Syntex: A service designed to analyze, categorize, extract and reuse content stored in Microsoft 365 using AI. For example, to extract content from invoices, receipts, identity documents or extract content from SharePoint document libraries, among others.
- AI Builder and Power Automate: To create document processing workflows with low code, allowing for example the validation of extracted data that can be exported to an ERP or other data storage systems.
- Azure Form Recognizer: Using machine learning, Azure Form Recognizer allows developers to create solutions that extract content from the documents they work with accurately with SDKs and REST APIs.
What do you think of all that intelligent document processing can do for you?
If you are interested in learning more about how IDP, RPA or AI technologies can help you optimize your operational management, do not hesitate to write to us, we will be happy to advise you and provide you with the most advanced solutions in the market.