From autonomous cars in motion to their digital twins in simulation, from the sensors that control them to the machines that make them, from trackside telemetry in motorsport, to R&D and aerodynamics in wind tunnels KX has the power and scalability to provide real-time analytics, instantaneous feedback and valuable insights into the vast amounts of data they produce.

Digital connectivity both within cars and across the full ecosystem of vehicles in motion from electric vehicles to electronic powertrains, to shared vehicles with their output from sensors is creating massive datasets.

Ingest, process, analyze data from connected vehicles in real-time and analyze history to predict and prevent failures with KX. Our platform can also be used to deploy advanced analytics and machine learning in vehicles. 

Most current manufacturing execution systems struggle with the bottlenecks of data being produced and their limitations inhibit the opportunity to exploit the rich value of that data in areas like fault detection, root cause analysis, and predictive maintenance.

KX, with its single integrated platform including its superior columnar-structured time-series database, enables you to scale from thousands up to hundreds of millions of sensors at any measurement frequency whilst maintaining extremely high levels of performance.

The growing volume of data in automotive environments provides new opportunities for predictive analytics and operational efficiencies in all areas from design and development to automation and supply chain management.

KX can capture, analyze and store high-frequency time-series data from thousands of sensors to compare with historical data in areas like fault detection and anomaly analysis. It includes a comprehensive suite of graphical tools with powerful OLAP drill-down capabilities to aid decision making based on historical and real-time data from multiple data streams.

Our technology platform can be used to analyze data from wind tunnels, trackside, roadside and satellite to assess performance, identify faults, predict potential failures, plan maintenance to improve design, optimize performance and reduce cost.

KX technology integrates with legacy systems and multiple data sources, allowing you to either augment or replace existing systems and libraries.

A connector framework simplifies integration and coexistence with incumbent systems.

APIs for .NET, Java, C, C++, Python, R, ODBC, Matlab and Excel.

Machine Learning capabilities using embedPy which loads Python into kdb+, allowing access to a rich ecosystem of libraries such as scikit-learn, tensorflow and pytorch.