Developed  a framework for data aggregation from diverse sources (IoT devices, satellites, supply chain systems).

Created AI-based taxonomy interpreter that maps activities to taxonomy criteria.

Automated report generation to align with regulatory requirements using NLP for document parsing and synthesis.

Integrated validation layers for audit-readiness and compliance accuracy.

Visualization Tools: Emissions reduction graphs, carbon credit usage heatmaps.

AI Predictive Models: Forecast future emissions and offsets.

Integration with Blockchains based traceability solution  : Verify and record carbon credits' authenticity and usage.

Data Integration: Pull data from offset projects (renewables, afforestation,EV usage etc.) and corporate operations.

Reinforcement Learning Models: Adapt strategies based on feedback loops.

Dynamic Goal-Setting: Adjust carbon reduction targets as efficiencies are achieved.

Continuous Improvement: Identify inefficiencies and propose automated corrective actions.

Cross-System Intelligence: Interlink energy use, logistics, and operational data to guide overall sustainability.