Real Estate, Facility & Energy

Utility Bill

Extract consumption, market location and cost data from electricity, gas, water and heating bills.

The Challenge

Every utility issues a different layout, and the identifiers that matter are easy to confuse — market and metering locations look alike but address different things. Prior-year comparison figures, estimated versus metered readings and multi-position tariff breakdowns all sit in the same document.

Industries

Real estate, facility management, energy management, multi-site operators.

Who Uses It

Facility/energy managers, finance, ESG/sustainability, controlling.

BASE Schema

Invoice number — Text

Invoice date — Date

Provider / utility — Text

Customer / contract account number — Text

Billing period — Key value set (from, to)

Market location (MaLo-ID) — Text

Metering location (MeLo-ID) — Text

Meter number — Text

Consumption — Number

Prior-year consumption — Number

Unit of measure — Enumeration (kWh, MWh, m³, GJ)

Energy class — Enumeration

Tariff components — Table

Net amount — Number

VAT — Number

Gross invoice amount — Number

Currency — Enumeration (EUR, USD, GBP, CHF, PLN, CZK)

CO₂ data (if shown) — Number

Recommended pipeline settings — Context (property → market location assignment and consumption plausibility ranges)

OPTIONAL Validation

MaLo-ID and MeLo-ID format validated; consumption compared against the prior-year period for plausibility; tariff positions reconciled to net, VAT and gross; billing period checked for gaps or overlaps.

Frequently ASked Questions

How can AI process utility bills across many properties?

It extracts consumption, tariff and cost per meter into structured data, enabling automated cost allocation and energy tracking across a portfolio.


Can utility-bill extraction support ESG and CO₂ reporting?

Yes — consumption and any stated CO₂ data are captured, feeding sustainability and energy-management reporting.


Why automate utility-bill processing?

It removes manual entry across hundreds of bills, catches consumption anomalies early, and underpins accurate service-charge settlement.

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