Reducing unplanned downtime across refinery operations
Shell engaged Aurelion to develop a predictive maintenance platform for a network of refineries operating across three continents. The challenge was integrating sensor data from legacy equipment with modern ML infrastructure to generate actionable maintenance signals before failures occurred.
We built an end-to-end pipeline ingesting over 40 million sensor readings per day, trained anomaly detection models on 18 months of historical failure data, and deployed an operations dashboard enabling maintenance teams to prioritise interventions with confidence.
Transforming asset management across a world-class real estate portfolio
EMAAR manages over 85 million square feet of prime real estate across the UAE, Egypt, India, and beyond, including some of the world's most recognised destinations. Sustaining the performance, safety, and energy efficiency of this portfolio at scale required a fundamental change in how asset data was collected, processed, and acted upon.
Aurelion built an AI asset intelligence platform integrating data from thousands of smart building sensors, maintenance records, occupancy systems, and energy meters. Predictive models now surface equipment failures weeks before they occur, optimise energy consumption in real time, and give portfolio leadership a live view of asset health across every market in the group.
Transforming project delivery with AI-driven risk intelligence
Large construction projects routinely overrun on cost and schedule. Heijmans engaged Aurelion to build a project intelligence platform that could identify delivery risks earlier, enable proactive intervention, and give leadership a unified, real-time view of portfolio health.
We built a platform aggregating data from project management systems, weather feeds, subcontractor performance records, and procurement systems to train risk classification models. The platform surfaces risk signals weeks before they would appear in traditional reporting, enabling project managers to act rather than react.
Building the governance foundation for responsible AI at scale
Philips operates in one of the most highly regulated sectors for AI. As the EU AI Act came into force and internal AI development accelerated, the organisation needed a governance framework that could scale with their ambitions without creating an innovation bottleneck.
Aurelion designed and implemented a comprehensive AI governance operating model including risk classification protocols, model lifecycle policies, explainability standards, and an internal review board structure. We also delivered an AI literacy programme reaching over 2,000 employees across R&D, clinical affairs, and regulatory functions.