Prototype 2025 Data Processing Emissions Accounting

ESG Emissions Data Tracker

AI-powered extraction, validation, and reporting of Scope 1-3 emissions data—turning messy corporate documents into audit-ready inventories.

The Challenge

Emissions data is messy, opaque, and time-consuming.
Regulatory pressure is mounting.

ESG emissions data comes from a wide range of unstructured corporate sources—utility bills, fuel receipts, travel logs, supplier invoices. Processing this manually is onerous for consulting teams and a bottleneck for commercializing emissions accounting software.

Emissions data scattered across PDFs, spreadsheets, and images
Manual processing is slow and error-prone—blocking commercial scale
New regulations require auditable inventories with full traceability
The Solution

Upload. Extract. Validate. Export.

An AI-powered workflow that ingests documents in any format, extracts emissions data with confidence scoring, enables human validation, and exports audit-ready reports—with full traceability throughout.

Concept Walkthrough

From document chaos to audit-ready data.

Dashboard Overview

Users see an overall view of ESG documents processed—by emissions scope category, site, or business unit. Real-time metrics on processing queue, accuracy rates, and pending reviews.

Dashboard Overview

Document Upload

Input documents can be uploaded individually or from predefined folders in batch mode. AI automatically detects document types and suggests scope categories.

Document Upload

AI Validation

Document validation view shows AI-generated summary of extracted data with accuracy confidence levels. Users can approve, edit, or flag AI-generated outputs for review.

AI Validation

Export & Reports

Extracted and verified emissions data can be exported into required output reporting formats. Summary metrics, scope breakdowns, and source document linkage included.

Export & Reports

Audit Trail

Full audit trail of all system activities and records maintained for compliance purposes. Every action logged—uploads, AI extractions, manual edits, approvals.

Audit Trail

Teams Integration

Same functionality available as MS Teams plugin via collaborative channels and tabs. Analytics dashboard, scope breakdowns, and export capabilities embedded where teams work.

Teams Integration
Key Capabilities

AI extraction. Human oversight. Full traceability.

Smart Document Ingestion

Upload utility bills, invoices, and fleet records in any format. AI automatically detects document types, extracts key data points, and suggests scope categorization.

Human-in-Loop Validation

AI-generated extractions include confidence scores. Users approve, edit, or flag outputs before final processing—maintaining quality and accountability.

Audit-Ready Exports

Every data point traceable to source documents. Full activity log for compliance. Export to standard reporting formats with complete provenance chain.

Technology

Built with modern AI tooling

End-to-end development using AI-assisted workflows—from specification through deployment.

M
Manus AI
MVP Spec & PRD
CC
Claude Code
Web App Prototype
N
Node.js
Frontend
Insights

What we learned

1

Perfect fit for agentic workflows

This use case lends itself well to emerging agentic functionality—parsing and interpreting different kinds of input ESG data, then normalizing outputs for final calculations.

2

Pattern applies broadly across ESG

Similar workflows exist for other ESG regulatory compliance topics where messy inputs are strewn across complex organizations and need to be managed and maintained accordingly.

3

Human-in-loop is non-negotiable

For compliance data, full automation isn't acceptable. The validation workflow with confidence scoring and explicit approval maintains the accountability regulators require.

4

Removes commercial bottleneck

Speeding up and making emissions data processing more efficient removes a key blocker to selling and commercializing broader emissions accounting software suites.