Revolutionizing Process Monitoring
Our goal is to bring advanced sensor technology and digital twin simulation across a variety of industrial applications. Currently in the phase of developing and testing prototypes and conducting pilot projects with industry partners.
1 High-Resolution Real-Time Monitoring & Advanced In-Pipe Sensor Precision
Industrial processes occur in closed systems—pipes, tanks, and reactors—where direct observation is nearly impossible. quantropIQ changes this by delivering high-resolution spatial and temporal data on multiphase flows, capturing both conductivity and capacitive (permittivity) changes in real time. This enables immediate process control and the detection of complex flow patterns. The advanced quantropIQ sensor, designed for in-pipe applications and certified with EX protection, can be used for controlling separators, measuring phase content and flow in distillation columns, monitoring chemical concentrations, ensuring product purity in multi-stage processes, measuring dissolved oxygen in bioreactors, optimizing fermentation, and many more.
2 Intelligent Process Optimization & Digital Twin Simulation
Beyond individual sensors, quantropIQ scales to an integrated sensor network deployed across an entire facility. Leveraging GPU-based parallel processing, the system creates a real-time digital twin of the production process by combining data from multiple sensors over space and time. This comprehensive overview enables end-to-end tracking of material flows and process conditions, supporting adaptive process control, early anomaly detection, and waste reduction. It works equally well for batch processes with frequent transitions and continuous processes requiring stable throughput.
3 Long-Term Data Analytics & AI Learning
Beyond real-time monitoring, quantropIQ transforms extensive process data into actionable intelligence through near-lossless compression and precise event labeling in the cloud. This long-term data analytics solution supports advanced applications such as predictive asset maintenance — minimizing downtime by anticipating failures before they occur — as well as formulation assistance for new product development, ensuring consistent quality and manufacturability. By refining production runs, energy consumption is optimized and scheduling becomes more efficient, which helps for high throughput with minimal waste. Over time, these self-learning models continually refine production strategies, transforming facilities into truly intelligent, data-driven ecosystems.
Interested in transforming your industrial process with AI-powered insights?
Join the journey: contact@quantropiq.com