Practical AI and analytics consulting grounded in real industrial environments — identifying high-value use cases, designing data infrastructure, and building the roadmap for predictive maintenance and operational intelligence.
Industrial AI delivers its greatest value when use cases are selected based on data availability and operational impact — not technology novelty. Rebus Novus helps clients cut through the hype and identify the AI and analytics initiatives that will actually move the needle on OEE, energy consumption, maintenance cost, or quality.
Our AI and analytics consulting begins with a structured use-case identification workshop: mapping your available data sources, assessing data quality and completeness, and scoring candidate use cases on feasibility, data readiness, and business value. Common high-value starting points include predictive maintenance for rotating equipment, energy anomaly detection, production yield optimisation, and quality control monitoring.
We then design the data infrastructure — historian strategy, data lake architecture, edge pre-processing, and the pipeline from OT data sources to analytics platforms. We are platform-agnostic and work across OSIsoft PI / AVEVA, Inductive Automation Ignition, PTC ThingWorx, AWS IoT, Azure IoT Hub, and open-source stacks.
For organisations at earlier stages of the data maturity curve, we provide KPI and dashboard design advisory — defining the right metrics, data collection points, and visualisation approach before investing in advanced analytics.
Tell us your application and challenge — our engineering team will recommend the right approach, technology fit and a clear roadmap, no obligation.