IPA Mailroom

Get your mailroom organized and more efficient with AI

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Imagine a world where you’re not losing time forwarding emails with inquiries that someone else should have received. Where you don’t have to manually save, rename and tag heaps of attachments ever again. It might seem like a distant dream, but artificial intelligence (AI) in your mailroom can make this a reality. By unleashing Intelligent Process Automation (IPA) with AI and machine learning (ML) on your digital or nondigital mailroom, this boring repetitive workload can be reduced by at least 50 percent. Read on as we turn fiction into fact.

Stemming the email flood

Even a digital Noah’s Ark probably couldn’t save us from the deluge of emails flooding our inbox. Oftentimes, either inquiries get forwarded endlessly until they reach the right people, or companies have a dedicated team that opens, reads and labels everything with metadata so that it can be processed and sorted. The latter is already a step up on the efficiency ladder. But both are time-consuming, repetitive and inefficient. Automation would not only result in a cost reduction, but also better customer service as questions get answered faster by the right person.

Intelligently sorting your mailroom

Quite a few companies already employ some form of manually programmed AI that sorts documents and mails. These algorithms usually generate metadata based on rules such as ‘does it contain word X or Y’ or formatting. This information is then used for sorting. However, it’s impossible to manually program for every possible variation in wording or layout. There is a need for human intervention at some point in the flow as we still do a better job at understanding and consequently sorting mails. But we can expand a computer’s comprehension capabilities by using Intelligent Process Automation backed by machine learning algorithms in your mailroom. This enables us to create a self-learning and fully automated process to extract data from mail, both physical and digital, and use this information to sort incoming inquiries.

Understanding mails and documents

Algorithms – and humans as well for that matter – will find it difficult to sort your incoming mail if they don’t understand its contents. Where previously computers were too ‘dumb’ to comprehend texts and images, advances in machine learning have partially removed this constraint. A number of techniques enable your intelligent process to understand contents:

  • Optical Character Recognition (OCR): through OCR it is possible to extract text from images. So, you can scan paper mail and turn it into digital text without having someone type it out manually. OCR can also be used to extract personal information from pictures of IDs or driving licenses.
  • Natural Language Processing: is the field of AI that focuses on the understanding of human language by computers. Through neural networks and deep learning, algorithms are much better at understanding text and can add more and accurate metadata without human intervention, even when the wording and formatting deviate from a standard template.
  • Facial recognition: can identify people in pictures or scans to automatically assign documents to the correct client record.

Sorting mails into the right folders and for the right people

In the next automation step, the information extracted by different algorithms is used as the basis for sorting and assigning the mails to the right people. The most potent type of machine learning for this phase is classification. These algorithms search for patterns in document characteristics to determine which set of characteristics qualifies a document to be sorted into a predefined category. A model trained with classification algorithms then takes these learnings and applies them to your incoming mail to sort them with great accuracy. Even if you’re at a loss when deciding which categories you need to sort into, machine learning can help. With clustering algorithms, ML can extract a set number of categories based on patterns that humans often can’t see. Once you’ve automated this extraction and sorting process with intelligent technologies, the outcome can serve as the basis for further automation efforts, such as the automatic naming of files.

Reducing workloads

The primary goal of a digital mailroom that incorporates artificial intelligence and machine learning is to reduce the administrative workload. In general, you see this diminishing by at least 50 percent, but ideally you can boost that number up to 75 or even 90 percent. This can have a number of advantages:

  • Cost reduction: as the same workload can be handled by fewer people.
  • More challenging work: instead of focusing on boring repetitive administration, your employees can focus on the core business of your company. Bank or insurance employees, for instance, have more time to advise their clients.
  • Increased customer satisfaction: their inquiries end up with the right person quicker than ever, so they are helped much faster too. Less administration also means more scope for providing personal advice and help. Both ultimately result in happier customers.

Stop dreaming of an intelligent mailroom. Turn fiction into fact and reach out to our experts, who’ll gladly help you stem the email flood.