From Reactive to Predictive — and Ultimately Generative
IB Flows is designed to move organizations beyond reactive data usage toward predictive and generative capabilities. By unifying disconnected systems, devices, and data sources into a single, trusted, and actionable data layer, the platform enables organizations to anticipate disruptions and automate optimization—without dismantling or replacing existing infrastructure.
Making Data Work Across Industrial Use Cases
In connected device environments, IB Flows consolidates fragmented telemetry, asset records, field service data, and usage signals into a coherent view of operations. This unified foundation enables predictive support models that shift service organizations from reactive response to proactive engagement. Early detection of emerging issues can reduce warranty costs by up to 35 percent, while data-driven maintenance recommendations and timely updates contribute to longer product lifecycles.
Industrial equipment optimization
For industrial equipment optimization, IB Flows bridges the long-standing divide between operational technology (OT) and enterprise IT systems. Real-time operational data is combined with enterprise context to prevent downtime through proactive intervention. Maintenance data is translated into automated actions that improve operational efficiency, while insights derived from real-world usage patterns and sensor anomalies help extend the lifespan of critical assets.
Open, Agile, and Economically Efficient by Design
IB Flows is engineered to maximize return on existing investments. The platform integrates with current systems at any level of data maturity, eliminating the need for disruptive “rip-and-replace” initiatives. By abstracting underlying stack complexity into reusable, consumable data products, it removes bottlenecks and accelerates the transition from concept to production.
Cost efficiency is embedded into the operating model. Organizations incur no upfront investment and pay only for what they consume, while reducing overall spend by eliminating redundant tools across the data ecosystem.
A Structured Path to Predictive Maintenance
IB Flows supports a step-by-step journey from raw operational data to fully operationalized, data-driven decisions. The process begins by connecting siloed data sources across manufacturing and device ecosystems without disrupting existing architectures. Reusable data products are then created, embedding business context, governance, and a comprehensive semantic model that accelerates innovation.
Once in place, these data products can be connected directly to AI models, intelligent agents, applications, and analytics tools. AI-ready data delivers measurable value within four to six weeks and can be scaled iteratively across the enterprise. Finally, insights are operationalized across maintenance, warranty management, quality control, and process optimization—enabling rapid experimentation and deployment without prolonged development cycles.