When you are in the research and development phase you need to figure out what works and more importantly, what doesn’t work. Reality AI allows you to track and detect specific events while building connected devices in a variety of applications. The company, originally designed for military use, is an engineer’s best friends when it comes to building IoT applications.
AlleyWatch spoke with cofounder and CEO Stuart Feffer about the company and about their first round of funding
Who were your investors and how much did you raise?
Our investors were primarily angels and family offices. We also had participation from TechNexus Venture Collaborative, a firm that works with corporate innovators and startups, based in Chicago. This was our Seed investment round.
Tell us about your product or service.
Reality AI is an AI-based signal processing engineer. Our product is used by companies creating connected devices and equipment products (industrial equipment, wearables, automotive components) that are instrumented with sensors and signals. Reality AI offers an application for R&D Engineers working to develop these products to create software that detects specific events and conditions in vibrations, sound, accelerometery, electrical signals, imagery, LiDAR, and remote sensing.
What inspired you to start the company?
The core technology behind Reality AI was originally developed for the US military and intelligence community. With the spread of ubiquitous sensors and the Internet of Things, we saw an opportunity to make these very powerful tools available to commercial and industrial customers and enable rapid development of powerful sensing applications in the Internet of Things.
How is it different?
Three things that are different about Reality AI:
1- We are not based on Deep Learning. We have our own approach to machine learning on sensors data that is grounded in the fundamental mathematics of signal processing. That means that we are more accurate and require much less data than deep learning on problems where our approach is a good fit.
2- Software-based detectors and classifiers built with our technology are suitable for real-time processing at the “edge”. Many of our customers can run their trained classifiers and detectors in firmware on inexpensive microcontrollers – no special hardware required.
3- We are focused on enabling other people’s products. Our customers are generally the R&D groups working on new products, and…