Acquiring Data: Addressing a Bottleneck
February 12, 2020
Despite all the advances in automation and digital technology, humans are still required to manually input information into computers. While modern technology makes automation easier than ever millions of hours are spent on data entry. Artificial intelligence and deep learning could be the key to ending data entry says Venture Beat article, “How Rossum Is Using Deep Learning To Extract Data From Any Document.”
Rossum is an AI startup based in Prague, Czechoslovakia, founded by Tomas Gogar, Tomas Tunys, and Petr Baudis. Rossum was started in 2017 and its client list has grown to include top tier clients: IBM, Box, Siemens, Bloomberg, and Siemens. Its recent project focuses on using deep learning to end invoice data entry. Instead of relying entirely on optical character recognition (OCR) Rossum uses “cognitive data capture” that trains machines to evaluate documents like a human. Rossum’s cognitive data capture is like an OCR upgrade:
“OCR tools rely on different sets of rules and templates to cover every type of invoice they may come across. The training process can be slow and time-consuming, given that a company may need to create hundreds of new templates and rule sets. In contrast, Rossum said its cloud-based software requires minimal effort to set up, after which it can peruse a document like a human does — regardless of style or formatting — and it doesn’t rely on fully structured data to extract the content companies need. The company also claims it can extract data 6 times faster than with manual entry while saving companies up to 80% in costs.”
Rossum’s cloud approach to cognitive data capture differentiates it from similar platforms due to being located on the cloud. Because Rossum does not need on-site installation, all of Rossum’s rescuers and engineering goes directly to client support. It is similar to Salesforce’s software-as-a-service model established in 1999.
The cognitive data capture tool works faster and unlike its predecessors:
“Rossum’s pretrained AI engine can be tried and tested within a couple of minutes of integrating its REST API. As with any self-respecting machine learning system, Rossum’s AI adapts as it learns from customers’ data. Rossum claims an average accuracy rate of around 95%, and in situations where its system can’t identify the correct data fields, it asks a human operator for feedback to improve from.”
Rossum is not searching to replace human labor, instead they want to free up human time to focus on more complex problems.
Whitney Grace, February 12, 2020
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