The state-of-the-art of software automation requires explicit programming by a developer. Tools that make this programming easier have gained popularity, but the paradigm is essentially the same: a human must program an automation step-by-step. This intricate, manual programming is time-consuming and error-prone, making automation prohibitively expensive for most of the world's businesses.
Our machine learning algorithms learn to automate work by continuously observing clicks and keystrokes and identifying repetition within this dataset. Once we understand a process, we can generate code for the automation. This approach dramatically broadens automation potential within a business. With Mimica, all of the low-volume, bespoke tasks that never warranted attention suddenly become viable candidates for automation.
The first product we've brought to market is an automated process mapping solution. Mapper sits on an employee's computer and continuously records their process for 2-3 weeks. Then our machine learning algorithms clean, analyze and merge the recordings into a single, elegant process map. These maps are used for RPA, time-and-motion studies, BPM and more.
Tuhin Chakraborty, CEO
Tuhin led software engineering teams at companies like Pandora and LinkedIn while spending nights and weekends building and selling enterprise software.
Raphael Holca-Lamarre, CTO
Raphael completed a PhD at the intersection of neuroscience and machine learning, developing brain-inspired learning algorithms for deep neural networks.