Sustainability / ESG8 weeks
AI for Carbon Footprint Tracking & Reduction
Client: Global Materials Co.
Measure and reduce corporate carbon footprint across complex supply chains and operations.
The Challenge
Global Materials Co. needed to help corporations accurately measure and reduce their carbon footprint across complex supply chains and internal operations. The challenge was to provide clarity on Scope 3 emissions and recommend effective reduction strategies.
Key Challenges:
- Accurately measure carbon footprint across complex supply chains
- Quantify Scope 3 emissions from suppliers and operations
- Model the carbon impact of different operational decisions
- Recommend effective reduction strategies
Without accurate carbon tracking, the company faced inability to meet sustainability goals, regulatory compliance risks, and missed opportunities for cost-effective emission reductions.
Our Solution
- AI-driven data aggregation platform collecting emissions data from multiple sources
- NLP extraction of emissions data from supplier reports
- Machine learning models modeling carbon impact of operational decisions
- Lifecycle assessment integration for comprehensive carbon accounting
- Recommendation engine suggesting most effective reduction strategies
- Dashboard visualization providing clear insights into carbon footprint
Technology Stack
PythonNLPScikit-learnLCA LibrariesPlotly/Dash
Client Testimonial
"Central to our net‑zero 2040 roadmap by clarifying Scope 3 emissions."
— Head of Sustainability, Global Materials Co.