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Digital customer service has a carbon footprint too.

AI requires computing power and energy. That's why we intend to measure Mira's footprint openly, explain our assumptions and use the results to reduce consumption — without confusing working hours saved with emissions saved.

Status: the method comes before the number.

Mira Omnia does not yet have a complete, verified carbon account. We will therefore not publish a CO₂ figure or any claim of savings until the underlying data, system boundaries and calculation method can be documented.

When the first inventory is ready, this page will show the period, scope, emission factors used, significant estimates and the most important reduction measures.

About us

Carbon accounting that can be verified.

Our method is based on the principles of the GHG Protocol and will be adapted as the standards evolve. The aim is comparable figures, clear boundaries and documented data sources.

Boundaries

We describe which activities and suppliers are included, so the accounts don't hide significant parts of our operations.

Data and factors

We use actual consumption wherever possible and convert it using dated, traceable emission factors. Estimates and assumptions are clearly marked.

Allocation and key figures

Shared operations are allocated using a described method. Beyond the total, we will track key figures such as the footprint per enquiry handled.

Improvement

The measurements should guide our choice of model, infrastructure and workflow — not just feed a report once a year.

What we will include.

A credible picture takes more than our own electricity use. We will therefore map relevant direct and indirect emissions across our operations.

Own operations

Energy, equipment and other activities that Mira Omnia controls itself.

Purchased energy

The energy attributable to our own operations and infrastructure.

The value chain

Cloud, AI processing, hosting, hardware, purchasing and other relevant supplier activities.

Customer-specific use

Consumption linked to actual processing, where supplier data and the measurement method make a meaningful allocation possible.