
TotalEnergies: Global Machine Learning Demand Prediction
Deploying cloud MLOps on Azure Databricks to predict global energy demand across 130 countries, replacing legacy bottlenecks with live intelligence.

Trusted by global energy producers, municipal utilities, and research centres




Operational Pressures
Energy and utility operators run high-stakes, 24/7 environments. Generic enterprise platforms struggle with the colossal volume of sensor time-series data, unpredictable consumption peaks, and strict statutory regulatory standards.
Razor builds bespoke, zero-failure systems. Whether engineering cloud-native Databricks pipelines to predict global demand patterns or modernising consumer-facing billing portals, we turn legacy friction into reliable commercial execution.
Architected for high-concurrency peak usage, disaster recovery, and continuous data ingestion.
Transparent machine learning workflows that provide full lineage, governance, and explainability.
Energy demand predicted with Azure Databricks MLOps for TotalEnergies.
Supported by South Staffs Water's resilient digital self-service tap.
Factory telemetry visualised live to eliminate peak industrial energy waste.
Continuous digital availability across mission-critical utility infrastructure.
Engineered Capabilities
Cloud-scale data engineering, applied machine learning, and human-centred portal design built for complex, regulated utility ecosystems.
Transform fragmented historical telemetry and consumption logs into automated machine-learning models that forecast energy usage across distributed territories.
Proven in Practice: TotalEnergies: Global MLOps pipeline on Azure Databricks forecasting consumption patterns across 130 countries.
Replace clunky legacy billing engines with intuitive, self-service portals designed for WCAG-compliant accessibility, live meter tracking, and automated payments.
Proven in Practice: South Staffs Water: Digital customer tap serving over 1.3 million water consumers with continuous resilience.
Hook edge meters and facility PLCs directly into unified real-time dashboards to spotlight energy anomalies, carbon footprints, and idle-state power waste.
Proven in Practice: AMRC Energy: Sub-metering telemetry transforming obscure power consumption into actionable facility intelligence.
Unify sensor data from heavy industry, substations, and microgrids to de-risk equipment maintenance and support data-backed net-zero transition roadmaps.
Proven in Practice: Industrial Decarbonisation: Combining edge sensor telemetry with cloud analytics to verify genuine efficiency gains.
Case Studies
Explore how we partnered with global energy leaders and water utilities to unlock actionable intelligence and enhance consumer service.

Deploying cloud MLOps on Azure Databricks to predict global energy demand across 130 countries, replacing legacy bottlenecks with live intelligence.

Architecting a scalable, self-service digital portal for 1.3+ million water utility consumers, modernising billing, meter submissions, and service requests.
Connecting factory sub-metering sensors to interactive visual dashboards, giving facility managers instant visibility over power spikes and equipment load.
Real feedback from leaders who partnered with Razor to modernise utility workflows and data architectures.

CEO, Advanced Manufacturing Research Centre (AMRC)
"When the CEO rings me and says, 'We thought we could do it 20 times quicker but have worked out a way to process it 4,000 times quicker' that's when you know you have partnered with the right team."

Global Energy & Infrastructure Systems
"Razor bridged the divide between complex data engineering and operational reality. Moving our machine learning models into robust MLOps gave us rapid, dependable forecasts across volatile international markets."
Whether you need to unify disparate telemetry feeds, legacy billing databases, and grid SCADA records into a board-ready 12-month AI roadmap, or deploy an automated telemetry classification model in 30 days, Razor delivers measurable momentum.
Strategic Discovery & 12-Month Roadmap
For energy, utility, and infrastructure executives looking to break down multi-system data silos, de-risk cloud data migration, and secure board alignment with a phased 12-month commercial roadmap grounded by an operational proof.
Operational Quick Win Powered by DataQI
Target a specific high-friction operational workflow—like predictive maintenance on pumping stations, meter reading discrepancy detection, or consumer demand anomaly classification. We deploy DataQI to deliver measurable ROI in 30 days.
From global Databricks predictive demand models to high-concurrency customer portals, our engineers deliver software that stands up to critical demand.