InfluxData and Litmus are integrating their respective data platforms to provide real-time edge AI for industrial applications. The collaboration combines InfluxDB 3 Enterprise with the Litmus Edge platform to provide a scalable system for collecting and analysing high-resolution time series data.

The integrated system is designed to handle the high frequency of data generated by modern industrial sensors, which can exceed the capacity of traditional data historians. Litmus Edge provides connectivity to more than 250 types of industrial equipment, including robotic systems and programmable logic controllers (PLCs), while InfluxDB manages the ingestion and real-time analysis of the resulting telemetry.

The companies are employing a hub-and-spoke architecture where data is processed and stored locally at the edge before being replicated to a central hub for long-term visibility. This model is intended to support predictive maintenance and anomaly detection by allowing teams to act on data within milliseconds of its generation.

“Integrating InfluxDB 3 Enterprise with Litmus Edge removes constraints so teams can operate directly on data at the source in real-time, with the precision required to power physical AI,” said Evan Kaplan, chief executive of InfluxData.

The solution is currently available for Litmus Edge deployments. The companies stated that the system uses advanced compression and object storage to retain high-resolution data more efficiently than legacy systems, facilitating the training of industrial AI models across multiple sites.