Monitor. Analyse. Save.

How Emma AI works.

Automated monitoring.
Practical action.

Emma AI analyses your meter data and emails practical recommendations to your team—helping you reduce energy waste, costs and carbon emissions.

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See what your team receives: consumption graphs, highlighted overconsumption and practical checks to help investigate energy waste.

Emma AI email showing an energy consumption graph, highlighted overnight overconsumption and recommendations to check equipment operating times.
Example Emma AI email. Site details removed.
Automated analysis. Straight to your inbox.

Your energy insights.
Delivered.

Emma AI analyses your sites’ meter data and emails clear, practical recommendations to help your teams reduce energy waste, costs and carbon emissions.

  • See the issue

    Consumption graphs highlight unusual usage.

  • Know what to check

    Practical recommendations guide your team’s next steps.

  • Reply with an update

    Report actions taken directly by email.

Tablet displaying an example Emma AI energy report with a consumption graph and recommendations.
Recommendations delivered by email—no dashboard login needed to read them.
How Emma AI works

Automated energy management.
Three clear steps.

Emma AI turns meter data into practical action—helping your teams reduce energy waste, costs and carbon emissions.

  1. Monitor

    Connect your meter data.

    Bring together half-hourly energy readings and compatible sub-meter data to understand consumption across your sites.

  2. Analyse

    Identify potential waste.

    Emma AI uses machine learning to identify unusual consumption patterns and flag opportunities for investigation.

  3. Save

    Turn insight into action.

    Site teams receive recommendations by email, take action and reply with updates to help reduce unnecessary energy use.

No dashboard login needed to read the advice. Recommendations reach your teams directly, while head office can review issues and responses across the estate.

Energy savings. Measurable impact.

Less energy wasted.
Lower costs. Lower carbon.

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Energy saved
34 GWh
Energy costs saved
£8 million
Equivalent carbon emissions avoided
4,216 tonnes CO₂e

Optimal Monitoring’s published cumulative savings to 31 December 2025. 34 GWh of energy, equivalent to £8 million and 4,216 tonnes CO₂e.

Explore customer case studies
Machine learning for energy management

Learns your sites.
Understands the context.

Emma AI combines meter data and site context to learn expected consumption patterns and improve its recommendations over time.

Starts with your meter data Existing half-hourly energy readings provide the foundation.

Your site’s context

Location, weather, time of day and site profiles help Emma AI distinguish expected demand from unusual usage.

Learning from feedback

Staff replies help refine the site profile, while anonymised comparisons with similar sites add further context.

Additional data sources

Compatible sub-meters, third-party systems and IoT devices can provide extra detail through supported data connections and APIs.

Additional devices are optional. Where suitable meter data is already available, Emma AI can work without new hardware.