There are a lot of commercial applications that are currently part of our everyday life. Think about Alexa, Siri or all the virtual assistants that pop up on websites or respond to our phone calls when we look for support. <\/p>\n\n\n\n
But when talking about business applications, especially in highly regulated industries, things are a little bit different. Are we ready to delegate critical decision making entirely to a computer? Are we confident the machine<\/em> will make the correct action or the accurate response for a specific step in the process? <\/p>\n\n\n\n In theory we shouldn\u2019t have doubts: a digital platform (the machine) that leverages AI\/ML technology can potentially automate any process. The key is the way in which the machine<\/em> will be programmed\/trained to execute the work. <\/p>\n\n\n\n There are three macro approaches to machine learning:<\/p>\n\n\n\n In today\u2019s business environment we must face multiple situations. Some of them are stable and pre-defined by third-party rules dictated by compliance requirements that must be met. Compliance requirements would have been harmonized with business logic and the customer\u2019s expectations. But when you started dealing with the customer\u2019s experience, this landscape became more dynamic and unpredictable.<\/p>\n\n\n\n AI\/ML technology can definitely improve scalability, precision and productivity, but depending on the application\/industry, the risk of false positive and\/or false negative could be too high and basically unacceptable.<\/p>\n\n\n\n At Papyrus Software<\/a>, the focus is on processes more than just technology. We believe in the power of people, in their knowledge and business skills, that\u2019s why we have developed a patented ML technology that learns from users and not just from data sets. <\/p>\n\n\n\n The combination of pattern recognition and process design provides the foundation to build solid business process automation<\/a> fueled by the user\u2019s knowledge during their executing of daily activities. <\/p>\n\n\n\n So, the machine<\/em> learns from actual events and transactions and from the ability of people to deal with exceptions and make correct decisions.<\/p>\n\n\n\n Once this partnership has been established, the collaboration between humans and the machine becomes mutually effective. The ability of the machine to connect an event with all possible solutions learned by experience will provide what we call Best Next Actions that support users across the entire organizations to take the best action in a particular situation, spreading this knowledge and competence to all decision making. <\/p>\n\n\n\n There are many ways to make innovations. Our way is to make value innovations,<\/em> building digital solutions and platforms that support companies to improve and modernize their Business Value Stream<\/a>. <\/p>\n","protected":false},"excerpt":{"rendered":" If you ask anyone to mention an innovative technology you will get the same answer 95% of the time \u2013 Artificial Intelligence. The other 5% will respond differently and more…Machine Learning and Robotic Process Automation<\/h3><\/p>\n\n\n\n
![\"Robotic](\"https:\/\/www.isis-papyrus.com\/e15\/images\/robotic-machine-learning.jpg\" "\\"Robotic")
<\/a>\n<\/div>\n\n\n\nUser-Trained Agent <\/h3><\/p>\n\n\n\n