IndustriesEnergy & Utilities

Intelligent infrastructure for critical operations

Real-time data platforms, predictive maintenance, trading systems and process automation, for industries where downtime is not an option.

50K+Assets monitored
35%Fewer unplanned outages
10M+Sensor readings/day
99.9%Operational platform uptime
// OUR DIFFERENTIATOR

Engineering for systems that cannot go down.

industry.approach
SCADA system integration
Time-series analytics at scale
Edge computing architecture
IoT data ingestion pipelines

IoT at industrial scale

Industrial assets don't announce failures, they signal them. Sciensa's IoT infrastructure captures these signals across 50,000+ assets, runs real-time anomaly detection and surfaces maintenance predictions before failures become outages. Global clean energy investment reached $1.8 trillion in 2023. (IEA (2024))

0M+Sensor readings processed daily
industry.approach
Failure prediction models
Maintenance scheduling optimization
Asset lifecycle analytics
Anomaly detection pipelines

Predictive maintenance, not reactive

Predictive maintenance is not about predicting failures, it is about eliminating unplanned downtime as a category. Sciensa's platform moves energy operators from reactive schedules to data-driven intervention windows. (WEF (2025))

0%Reduction in unplanned outages
// WHAT WE DELIVER

Engineering for critical infrastructure

Where downtime is not an option, we build resilience.

Critical Operations Systems

SCADA integration, real-time operational dashboards and alert management for energy generation, transmission and distribution.

  • SCADA integration
  • Real-time dashboards
  • Alert management
  • Operational intelligence

Real-Time Data Platforms

IoT data ingestion, time-series analytics and operational intelligence platforms processing millions of sensor readings per second.

  • IoT data ingestion
  • Time-series analytics
  • Sensor data pipelines
  • Edge computing

Predictive Maintenance

ML models for equipment failure prediction, maintenance scheduling optimization and asset lifecycle management.

  • Failure prediction
  • Maintenance scheduling
  • Asset lifecycle
  • Anomaly detection

Energy Trading Platforms

Market data integration, automated trading systems, risk management and regulatory reporting for energy market participants.

  • Market data integration
  • Automated trading
  • Risk management
  • Regulatory reporting

Process Automation at Scale

Field workforce management, work order automation and process orchestration for large-scale utility operations.

  • Field workforce management
  • Work order automation
  • Process orchestration
  • ESG analytics
// CASE STUDIES

Results in production.

National Grid Operator

Predictive Maintenance Platform

ML predictive maintenance reduced unplanned outages by 35% and maintenance costs by 25% across 50K+ monitored assets.

Predictive MaintenanceIoT Data
Energy Conglomerate

Real-Time Operations Platform

Unified operations platform processing 10M+ sensor readings/day with real-time alerts and 99.9% system availability.

Critical OperationsReal-Time Data
Renewable Energy Company

Energy Trading System

Automated trading platform with risk management and regulatory reporting, processing 500K+ daily trading events.

Energy TradingProcess Automation
Lumia AI

AI intelligence for critical energy and utilities assets.

Lumia AI brings predictive maintenance, anomaly detection across 50K+ assets, energy trading analytics and automated ESG reporting.

Explore Lumia AI

Módulos & capacidades

Per-asset predictive maintenance
Real-time IoT anomaly detection
Energy trading analytics
Generation dispatch optimization
Energy demand forecasting
Automated ESG reporting
Operational efficiency monitoring
Production model observability

// FAQ

Frequently asked questions.

Reactive maintenance fixes equipment after it breaks. Preventive maintenance services on a fixed schedule. Predictive maintenance uses sensor data and ML to identify the specific signature that precedes a failure, scheduling maintenance only when needed.

IoT sensors capture operational data, temperature, pressure, vibration, current draw, at high frequency. The platform aggregates data across thousands of assets, runs anomaly detection and surfaces alerts before failures occur.

Edge computing processes data close to where it's generated rather than sending all data to a central cloud. Some decisions require sub-second response times that cloud round-trips can't achieve. Edge and cloud work together.

High-throughput ingestion pipelines, time-series databases optimized for sensor data, streaming processing for real-time anomaly detection, and visualization that allows navigation from fleet-level overview to individual asset detail without latency.

Energy trading platforms manage buying and selling of electricity across spot markets, futures and bilateral agreements. Data intelligence improves trading by forecasting variable generation (wind, solar), predicting consumption patterns and optimizing bidding strategies simultaneously.

Ready to modernize your energy infrastructure?

Talk to our team about your operational platform and predictive analytics challenges.