DataPilot

Modern vehicles generate massive sensor data (hundreds of thousands of data points per second), scaling to gigabytes per day and petabytes across fleets. This data is essential for machine learning applications like driver-assistance systems, predictive maintenance, and performance optimization. However, raw vehicle data is highly inconsistent and unstandardized, requiring time-consuming manual mapping and cleaning. Data quality issues (e.g., missing values, spikes, faulty readings) can silently degrade model performance and pose safety risks. Current manual, fragmented data preparation processes are inefficient, costly, and lack transparency, creating a need for automated, standardized solutions. DataPilot is a novel deeptech software platform that introduces a new paradigm for preparing automotive sensor data for machine learning by tightly integrating domain intelligence, explainable validation, and automated contextual understanding into a single system. It constitutes the first physics-informed automation engine that transforms raw time-series data into high-quality, model-ready datasets.