HiveMQ Pulse

Organizations that generate large volumes of operational data often struggle to extract actionable insights from their data streams. Industrial operations can produce massive amounts of raw data from sensors, equipment, and processes. This data typically exists in disconnected systems without the context needed to make operational decisions. Traditional solutions that move raw data to cloud systems for processing create delays that can make insights available too late to be useful.

HiveMQ Pulse processes and contextualizes data where the data is generated, not in the cloud. The HiveMQ Pulse platform applies consistent data models across your entire infrastructure to transform raw measurements into meaningful business information in real-time. It provides a shared space for managing data and applies standard data models to transform and enrich it. These functions are distributed across the system, which removes the need to process everything in the cloud.

This distributed approach delivers real-time information across your organization and supports use cases such as predictive maintenance, automated alerts, and AI/ML training without slow cloud batch processing. By standardizing data formats and adding business context at the source, HiveMQ Pulse helps bridge the gap between operational (OT) and information systems (IT).