We turn decades of hard-science expertise — first-principles physics, signal processing, and modern AI — into engineering solutions you can trust. From vibration modeling to environmental sensing, we build systems grounded in real physical accuracy, not just correlation.
We bring decades of proven signal-processing expertise directly into IoT sensing applications. By transferring established techniques — adaptive filtering, spectral analysis, noise reduction — into connected devices, we help you extract cleaner, more reliable data from low-power, resource-constrained sensors, without reinventing the algorithm from scratch.
Ideal for: connected device manufacturers, industrial IoT, wearables, and smart infrastructure — anywhere edge sensors need smarter, more efficient processing.
We build engineering solutions grounded in first-principles physics — finite-difference vibration modeling, elastic and electromagnetic wave interpretation, and other "hard science" capabilities most data science teams simply don't have. When your sensor data needs a real physical model behind it, not just statistical correlation, that's where we come in.
Ideal for: industrial IoT, robotics, structural health monitoring, and geothermal/energy applications — anywhere physical accuracy matters as much as predictive power.
We combine modern sensor networks, edge computing, and AI-driven analytics to turn raw environmental signals — air quality, water conditions, seismic activity, weather, soil health — into actionable insights. From real-time acquisition to predictive modeling, we help you move beyond static monitoring to systems that detect and forecast.
Ideal for: environmental agencies, agriculture, energy and utilities, and smart cities — anywhere real-world conditions need to be measured, understood, and acted on.