How Carbonly turns source documents into traceable Scope 3

The hard part of Scope 3 is not the arithmetic, it is getting a physical quantity out of a supplier document and proving later where it came from. Here are the twelve steps that happen without anyone asking, and what each one does to keep the number defensible.

What happens to your data without you doing anything

1. Your documents arrive automatically

Subcontractor invoices, concrete dockets, EPDs and utility bills flow in from email, OneDrive, or SharePoint. Each project gets its own email address. No login needed from site managers.

2. AI reads every document

PDFs, images, Excel, scans. Eight file formats, any supplier. Extracts quantities, dates, supplier details, then matches each line item to the correct NGA emission factor.

3. Every extraction is verified

Five automated checks: duplicate detection, unit compatibility, quantity outlier analysis, date validation, content verification.

4. Materials matched automatically

Five-tier matching cascade. When a reviewer corrects a match, the line text is saved as an alias for your organisation.

5. Data quality checked daily

Deterministic anomaly checks run daily at 6am and after each document batch, and the Data Health Agent reports coverage gaps and stale data.

6. Trends explained, not just shown

When emissions change period over period, the system decomposes the variance into specific contributors.

7. Reports pre-generated

NGER reports pre-populated with per-facility, per-gas breakdowns. AASB S2 disclosures linked to your metrics.

8. Emission factor versions recorded

Each record keeps the emission factor version it was calculated with, so a new NGA edition does not silently change historical numbers.

9. Audit pack ready on demand

Every number traces to a source document. Designed to support ASSA 5010 assurance.

10. Deadlines tracked proactively

NGER October 31. AASB S2 aligned to your FY. Safeguard on the NGER reporting year.

11. Ask questions in plain English

Carbonly Copilot answers questions about your emission data instantly.

12. Duplicates caught across documents

Cross-document correlation identifies when the same transaction appears in multiple uploads.