A study carried out by OnePoll of more than 10,000 office workers from different countries revealed that workers spend an average of three hours a day at the computer performing repetitive tasks that have little or nothing to do directly with their work and that are prone to human error, reducing that time of tasks that add more value to the organization and more professional satisfaction. 

And what is the most hated task? Data capture. Followed by mail management, cataloging digital documents (in excels, images or PDFs), IT and software reports and invoice management are the five most detested tasks. 

Automation through AI

The great solution to all these back office problems goes through automation, which uses artificial intelligence and machine learning technologies to reduce response times, time spent on tasks and improves the accuracy ratio, eliminating the human error factor. 

These tasks are often full of unstructured data that make it difficult to manage. What is unstructured data? They are those raw or disorganized data that cannot be easily stored in predefined structures. A very simple example to understand the difference: if we enter data through a form on a website, the collection is done in a uniform way and the data is preformatted. However, if we have to extract data from a text document, for example, a set of personal data in the body of an email, those are unstructured data that we must process and structure manually by assigning a structure or classification. 

In what cases can we see this technological solution applied? At Keepler we have developed a solution that uses artificial intelligence and that streamlines the implementation of projects for this type of tasks. Here are some of the most common use cases: 

Billing processes: It is possible to extract entities from documents or invoices and reduce manual inspection time. In addition, it enables its integration into the corporate ERP, thus reducing the possibility of errors and allowing the automation of this process. 

Sorting emails: Receiving hundreds or thousands of emails can create an excessive sorting and management workload for customer service departments. Automating analysis and assigning it to the corresponding department reduces cost and time, in addition to automatically detecting and discarding spam emails, thus reducing a considerable number of emails.

Revisions of texts and versions: Legal contracts, regulations, official gazettes … All types of evolving documents require dedication to keep up to date. With the help of AI technologies it is possible to summarize documents and obtain new information, comparing it with older versions, thus improving cost efficiency in comparison to manual performance.

Image: Unsplash | @kaitlynbaker


  • Adelina Sarmiento

    CMO at Keepler. "My experience is focused on corporate communications and B2B marketing in the technology sector. I work to position Keepler as a leading company in the field of advanced data analytics. I also work on a thousand other things to make Keepler a top company to work for."