About Workshop
Enterprise LCA Automation: Building AI-Powered Dashboards for CBAM & Scope 3 Compliance is a hands-on professional workshop focused on using AI, Python automation, and dashboards to simplify carbon accounting, Scope 3 tracking, and CBAM compliance.
Participants will learn to automate supplier data collection, clean procurement records, map emissions categories, calculate embedded emissions, and generate audit-ready compliance reports. Across three days, they will work with Python, ETL tools, AI/LLM APIs, SQLite, Streamlit, and Plotly to build an end-to-end carbon compliance automation workflow.
Aim
The aim of this workshop is to equip participants with practical skills to automate LCA, Scope 3 carbon accounting, and CBAM compliance workflows using AI-powered data pipelines, emissions calculation engines, and interactive dashboards.
What Participants Will Learn
- Understand automation in LCA, Scope 3, and CBAM compliance reporting.
- Build Python-based pipelines for procurement and supplier data processing.
- Map transaction data to GHG Protocol Scope 3 categories.
- Use AI/LLM tools to classify supplier descriptions, BOMs, and import items.
- Develop embedded emissions calculation logic using supplier data and benchmarks.
- Track data quality, source records, calculation tiers, and audit readiness.
- Build Streamlit dashboards for executive reporting and supplier analysis.
- Generate structured compliance-ready reports and XML/JSON-style outputs.
- Forecast carbon certificate exposure and compliance risks.
- Create a prototype AI-powered carbon compliance dashboard.
Structure
📅 Day 1: Automated Scope 3 Data Ingestion & Data Cleansing
Core Objective: Eliminate manual CSV uploads by building automated pipelines that ingest, clean, and map multi-tier supply chain data for enterprise Scope 3 carbon accounting.
- Automating data extraction from Enterprise Resource Planning systems and procurement ledgers
- Programmatic handling of missing supplier data and anomalous emissions factors
- Mapping raw transaction logs to standardized GHG Protocol Scope 3 categories
- Structuring transactional data into production-ready dataframes for carbon modeling
- Cleaning multi-currency procurement datasets for emissions calculation workflows
- Creating automated baseline Scope 3 footprint calculations using spend-based emission factors
🛠️ Hands-on Activity:
- The Procurement-to-Carbon Pipeline: Participants will ingest a raw, multi-currency corporate procurement dataset, programmatically clean formatting errors, map transactions to Scope 3 categories, and automatically calculate a baseline Scope 3 footprint using standard spend-based emission factors.
🧰 Tools Covered: Google Colab, Python, Pandas, NumPy, Openpyxl, Open-Source ETL Frameworks
📅 Day 2: AI-Powered LCA & CBAM Embedded Emissions Engine
Core Objective: Build a calculation engine that automatically maps complex bill-of-materials data to specific EU Customs CN codes and applies strict Monitoring and Reporting Regulation formulas.
- Using LLMs through free API tiers to parse unstructured supplier descriptions
- Auto-classifying imported items into relevant CBAM CN codes
- Understanding direct and indirect embedded emissions calculations for CBAM reporting
- Applying programmatic logic to choose between supplier-specific primary data and EU default benchmarks
- Tracking calculation tiers, source data origins, and audit trails for third-party verification
- Creating a structured emissions engine for steel, aluminum, cement, and other CBAM-relevant goods
🛠️ Hands-on Activity:
- The Autonomous CBAM Auditor: Participants will build a Python function that uses a free, open-source AI model to categorize raw import line-items into correct steel, aluminum, or cement CN codes, then calculate embedded carbon intensity and financial certificate exposure.
🧰 Tools Covered: Google Colab, Groq API, Hugging Face Transformers, Python Core Logic, SQLite
📅 Day 3: Building the Audit-Grade Compliance Dashboard
Core Objective: Convert complex Python backend calculations into an interactive, enterprise-ready analytics dashboard that legal, finance, and sustainability teams can use for regulatory reporting.
- UI/UX fundamentals for corporate sustainability and compliance reporting
- Balancing high-level executive KPIs with granular regulatory reporting views
- Building drill-down tables to track supplier response rates and missing verifications
- Identifying high-exposure carbon leakage points across supplier networks
- Generating compliant XML and JSON payload exports for EU CBAM registry workflows
- Creating real-time financial forecasting views for quarterly certificate accrual planning
🛠️ Hands-on Activity:
- The One-Click Executive Compliance Hub: Participants will assemble a web-based Streamlit dashboard that displays interactive maps of carbon intensity across global supplier networks, flags missing supplier verifications, and includes a download button for an audit-grade carbon declaration report.
🧰 Tools Covered: Google Colab, Streamlit, Plotly Express, Python, GitHub
Important Dates
Registration Ends
4:30 PM IST
Workshop Dates
2026-06-25
5.30 PM
5.30 PM
What You Will Gain
Outcomes
- Build automated Scope 3 data ingestion and cleansing pipelines.
- Process procurement datasets for carbon accounting.
- Convert transaction records into emissions-ready dataframes.
- Estimate baseline Scope 3 footprints using emission factors.
- Use AI to classify supplier and import data for CBAM-related categories.
- Build a CBAM embedded emissions calculation engine.
- Compare supplier-specific data with default benchmarks.
- Maintain audit trails for verification and compliance.
- Create interactive dashboards using Streamlit and Plotly.
- Generate KPI views, supplier drill-downs, exposure charts, and reports.
- Understand how AI and LCA automation support enterprise carbon compliance.
Who Should Attend
- Ideal for professionals, researchers, and students interested in AI-enabled sustainability reporting.
- Suitable for learners working in carbon accounting, LCA automation, and CBAM compliance.
- Designed for participants who want hands-on experience with Python, AI tools, and dashboards.
- Helpful for those solving real-world environmental, supply chain, and compliance challenges.
- Relevant for anyone looking to automate carbon reporting and improve sustainability data workflows.