AI Carbon Tracking
Emissions measured continuously from operational data, so carbon numbers are managed like a metric instead of estimated like a memory.
Most companies measure carbon the way they measured finances before ledgers: once a year, from estimates, with spend-based averages standing in for what actually happened. We build AI carbon tracking for ESG-driven organizations that treats emissions as live operational data. Extraction models pull activity data continuously from meters, fuel systems, logistics records, and supplier invoices. Calculation engines apply versioned emission factors and flag where a spend-based estimate can be upgraded to real activity data. Anomaly detection catches the leaking valve, the idling equipment, and the data error before they distort the annual number. The result is a carbon position you can see monthly, steer with, and hand to an assurance provider with the lineage intact, from disclosed figure back to source record.
Connect meters, fuel systems, logistics data, and supplier invoices so activity data flows in continuously rather than annually.
Calculate emissions with versioned factors and methods, upgrading spend-based estimates to activity data wherever it exists.
Detect anomalies in the emissions signal, catching operational issues and data errors within days instead of at year-end.
Serve live dashboards against reduction targets, with assurance-ready lineage from every figure back to its source.
What it does
Continuous activity capture
Pulls fuel, energy, and logistics activity data from operational systems and documents as it is generated, with citations.
Versioned carbon accounting
Emission factors and methodologies are versioned per calculation, so every figure is reproducible and restatements are explainable.
Emissions anomaly detection
Flags unexpected jumps in the emissions signal, surfacing leaks, idling equipment, and data errors while they can still be fixed.
Target tracking
Live progress against science-based and internal reduction targets, by site and business unit, so accountability has a dashboard.
An industrial operator moved 60 percent of its Scope 1 and 2 reporting from annual estimates to continuous measurement and found a compressed-air leak worth 200 tonnes of CO2e a year in the process.
Questions, answered
The annual exercise is a reconstruction from estimates. Continuous tracking measures emissions from live operational data, so you can manage the number during the year, catch anomalies early, and report from records instead of recollections.
Yes, pragmatically. Supplier invoices and logistics data feed activity-based calculations where possible, spend-based methods fill the gaps, and the system records which method backs each category so upgrades are visible over time.
That is the design goal. Every figure carries lineage from disclosure back through a versioned calculation to a cited source record, which is what assurance providers ask for first.
Directly. The tracked carbon data feeds disclosure frameworks like CSRD and GRI as a governed dataset, so reporting draws from the same numbers operations manage against.
Bring ai carbon tracking to your team
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