CarbonLedger

CarbonLedger is a web app (with optional API integrations) that helps companies build audit-ready evidence packs for science-based targets. Instead of trying to “do all carbon accounting,” it focuses on the painful middle: proving data lineage, assumptions, and calculation logic behind Scope 1–3 baselines and target pathways. Users import activity data from ERP/procurement and emissions factors from approved libraries, then the app auto-generates a traceable chain: source file → transformation steps → factor selection → calculation → versioned outputs. It flags common SBT submission weaknesses (missing boundary notes, inconsistent base-year recalculations, supplier data gaps) and produces reviewer-friendly exports (method statements, change logs, and QA checklists). It’s a combination traditional + AI app: AI assists with mapping messy procurement line items to categories, drafting methodology narratives, and spotting anomalies, but humans approve everything. This is not glamorous; it’s compliance plumbing that reduces rework and embarrassment.