Energy data ETL
Pipelines that ingest, cleanse, align and structure market, meter, inverter and weather data into analytics-ready datasets, in streaming and batch.
Data and AI for energy operations.
Unified data pipelines, machine-learning forecasts, preventive maintenance and storage optimisation, delivered on AWS with live energy-sector implementations behind them.
Our experience
Our experience in energy covers data pipelines, forecasting and consumption monitoring, preventive maintenance, storage optimisation and AI assistants for operators. The sections below describe the problems we help solve.
Challenges in the sector
Data scattered across sources
Energy exchanges, smart meters, inverters and weather feeds arrive in different formats and at different times.
Uncertain generation and demand
Solar and wind output and consumption are hard to predict without models that combine weather and history.
Unplanned failures and energy loss
Abnormal patterns in production data are easy to miss until they become outages.
Storage decisions that ignore the full picture
Charge and discharge choices depend on prices, forecasts, consumption and battery degradation together.
Where we can help
Forecasting and consumption monitoring
ML models that predict solar and wind output per site, with real-time consumption monitoring and recommendations for corporate clients.
Anomaly detection and preventive maintenance
Continuous monitoring of performance, weather and component health to detect abnormal patterns and predict failures before they occur.
Smart battery storage optimisation
Charge and discharge management driven by market prices, generation forecasts and consumption, with battery degradation built in.
Conversational AI assistant
A text and speech agent that answers operational queries from live energy data and ML forecasts, across multiple sites.
Evidence
- Live implementations in the energy sector
- AWS Advanced Tier Services Partner
Related services
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