The Importance of Combining Intelligent Document Management with Low-Code Software

Combining intelligent document management with a low-code platform will help companies to significantly improve efficiency and productivity, as all their processes and applications involving any type of documentation will be optimized.

Companies work with different types of documents: invoices, contracts, payroll, accounting documents, quality management, occupational risk prevention, time recording, etc. Companies need to organize and store these documents for different purposes: payment vouchers, receipt or dispatch of goods, legal issues, etc.

Often, these documents are received in paper format and it is necessary to file them digitally or make a note in our computer system of the physical location of the document.

Many companies still carry out these procedures manually, or at best use optical character recognition (OCR). Unfortunately, both strategies are costly and time-consuming, and generally create bottlenecks.

I strongly believe that there is a better way to solve this problem! The solution is to combine various technologies such as low-code software and artificial intelligence.

Document management today

As mentioned previously, in all companies there comes a moment when they must input a file in the computer system, and most of the time it is done manually. Admittedly, some companies may argue that they do not receive enough documentation to merit change, but we can all agree that assigning a routine task to a person can increase the risk of errors. If we are talking about managing a high volume of documents, this is completely unfeasible.

Some companies have tried to solve this problem by using OCR, but this system also has some disadvantages associated with the quality and resolution of the images:

  • Damaged original documents.
  • Blurred or unclear handwriting.
  • Low image resolution.
  • Stains or transparencies on the paper.
  • Unusual typography.
  • Document dimensions.

Taking document management one step further

Automating a document management process, especially if we are dealing with large quantities of documents, requires:

  • Classifying incoming documents, extracting the data, and storing it in a database in a structured manner.
  • A team of people to receive and solve the incidents that are reported during the automatic data extraction process.
  • A user interface to validate and combine the information.

From a technical perspective, we realize that we are talking about digitalizing all the above factors. Therefore, we will need a platform that can generate new applications in an agile way and has the capacity to integrate with other technological solutions.

It is true that integration with OCR could make our work easier, but there are already other technologies related to artificial intelligence that can contribute in a more significant manner.

Today, it is already possible to use natural language and machine learning technologies to help classify and extract information from documents. Machine learning services can understand our documents as key/value pairs (Invoice No.: 19562887), so they are able to interpret the different types of documents better than OCR.

However, machine learning is just one piece of the puzzle and can be an enabler within our workflow. When we design our process with application development software, we must consider that this automation may cause incidents that will need to be resolved by the team. In addition, we should leverage each incident by reporting feedback for our automatic learning system.

In most cases, the process of data extraction and classification is only the tip of the iceberg, as there may be many more steps before and after the document management process. In conclusion, a low-code tool like AuraPortal proves invaluable for the end-to-end automation as it empowers companies to easily implement all the necessary processes and applications in an agile way, and seamlessly integrates with other tools like RPA, ERP, etc.

Tomás Martí