Stabilise production. Optimise every MWh.

In industrial energy systems, performance depends on continuous trade-offs between efficiency, flexibility, asset availability and economic constraints.

Indao transforms your operational data - production, utilities and energy assets - into reliable decision-making reference points to improve efficiency, operational stability and energy efficiency, without adding operational complexity.

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Indao turns this energy complexity into measurable operational decisions.

Measurable results

More robust energy decisions, based on your operational data

Global view of energy performance

Correlation between production, consumption and operational constraints

Optimised energy efficiency

Reduction of losses and improvement of overall system efficiency

Anticipation of performance deviations

Early detection of anomalies before economic or operational impact

Why doing nothing has become a risk

Energy systems are becoming more complex to manage

Energy cost volatility

Need for rapid trade-offs between production, consumption and flexibility

Pressure on environmental performance

Reduction of emissions and improvement of energy efficiency

Multiplication of energy sources

Integration of new vectors and production variability

High availability requirements

Operational continuity and reliability of critical assets

Where Indao creates value in the energy sector

Analytical levers tailored to each energy segment

Cogeneration

Optimise thermal and electrical control to maximise overall efficiency and energy recovery

HVAC

Dynamically adjust heating and cooling production based on real needs to reduce consumption and deviations

Green hydrogen

Improve operating condition stability and energy efficiency of production units

Wind energy

Analyse operational performance to improve asset availability and energy yield

Boilers

Optimise combustion and thermal efficiency to reduce energy losses and improve operational stability

A performance-driven analytical approach

Indao enables energy teams to make faster decisions and manage their installations more precisely.

Identification of interactions between asset behaviour and energy efficiency
Identification of early signals indicating performance degradation
Transparent analyses supporting technical validation and operational management
Translation of insights into concrete operational actions

See clearly. Act decisively. Optimise sustainably.

Decisions that have already proven their impact

  • Process Performance Optimization

2Valorise

Optimising the steam network to maximise cogeneration plant performance
  • Energy

CoCEPTIO

Structuring and leveraging HVAC data to improve energy efficiency
  • Process Performance Optimization

CRM Group

Identifying key parameters in hot rolling to better control process performance
  • Data-driven Decision-Making

EKO-MYŚL

Centralising waste and energy data to improve operational control

Want to make decisions differently?

Let’s explore how your data can become a concrete operational lever.

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Indao is not just a monitoring tool: it is an advanced analytics platform that transforms industrial data into concrete, actionable recommendations. Where SCADA or ERP systems collect and display data, Indao helps your teams gain clarity, take the right actions and optimise operations sustainably.

Deployment is fast and progressive. On average, 4 to 6 weeks are enough to connect your first data sources, build the models and launch the first dashboards.

The platform is modular: you can start with a targeted pilot on a critical asset, then progressively extend it to other lines, sites or countries.

Indao is designed for the entire manufacturing industry and industrial infrastructure.

The platform adapts to a wide range of sectors, processes and equipment, wherever industrial data is available.

ROI is assessed based on concrete indicators: operational performance, asset availability, energy consumption and product quality.

Indao structures the business case from the outset and enables tracking of actual gains over time.