Our expertise ranges from hard real-time FPGA solutions to secure, high-uptime cloud deployment of predictive AI. We focus on developing custom software solutions for industrial applications at both full-scale and at the prototyping/testing stage. We have the infrastructure and expertise to support the design and testing of tightly integrated electro-mechanical systems.
We specialize in developing embedded software solutions and real-time controllers. Common data and control platforms that we work with include Speedgoat systems, National Instruments CompactRIO, or the Bachmann M1 target. We have experience interfacing with a wide range of sensors, often for real-time control, including inertial measurement units (IMU), pressure sensors, force sensors, laser Doppler anemometers, or velocimeters.
Our hardware-software interface work is facilitated by our expertise in implementing highly scalable and distributed data storage solutions. We have successfully completed numerous projects performing real-time data analytics and machine learning on IoT data by leveraging cloud services such as AWS. We make sure that the software we develop is scalable, modular, and easy to maintain. For this, we often leverage microservice architectures using technologies such as Docker and Docker Swarm. We have extensive experience using MEX, allowing us to interface low-level (C/C++/Fortran) components to MATLAB.
We use MATLAB and Simulink in at least four distinct ways:
We have used MATLAB and Simulink for many years across various sectors ranging from commercial multi-MW battery assets to government supported cutting-edge R&D. Perhaps our strongest offering is a deep understanding of Simulink data structures (such as busses and vectors) and how they translate into real-time usable code via Simulink Coder™ and Simulink Real-Time. Our deep understanding in this area means that we can design MATLAB, Simulink, and Stateflow® code with a real-time/embedded requirement in mind.