Machine Learning (ML) takes Robotic Process Automation(RPA) to the next level. In essence, RPA handles processing data (gathering, sorting, calculating and reporting), while ML begins to use it and mine it for its valuable insights. Automated processes operate based on the continuous analysis of incoming information, and learn to act smarter over time. This is especially beneficial for businesses dealing with large volumes of unstructured data, such as images, video and audio files and text files like PDF documents. ML is capable of gathering insights and improving them over time, while RPA executes them, working in tandem for best results.
Depending on the exact nature of the task, our experts choose the type of automation with the best ratio of added value to cost of implementation. ML requires a larger investment than RPA, due to training data, a more robust infrastructure, and development work provided by highly skilled experts. The ROI is well worth it, however, thanks to deeper insights, better automated decision-making, and the ability to analyze both structured and unstructured information.