Mavarick offers an AI-powered sustainability management platform specifically engineered for enterprises navigating intricate supply chains. It streamlines Environmental, Social, and Governance (ESG) compliance by automating the challenging processes associated with Scope 3 emissions tracking. The platform manages the complete lifecycle, encompassing the collection of supplier data, calculation of emissions based on industry standards, generation of audit-ready reports, and provision of AI-driven decarbonization recommendations.

Developed by specialists in supply chain management, climate science, and artificial intelligence, Mavarick aims to simplify sustainability reporting. It integrates smoothly with existing enterprise resource planning (ERP) systems, procurement tools, and transportation management systems (TMS), ensuring accurate data flow without reliance on manual uploads. This automation enables organizations to focus on achieving sustainability objectives and net-zero targets, particularly addressing complex Scope 3 categories such as purchased goods and services, and upstream transportation and distribution.

Avarni offers an advanced carbon accounting software solution powered by Artificial Intelligence, specifically engineered to assist enterprises and consulting firms in navigating the complexities of mandatory climate reporting. The platform transforms the often burdensome task of climate disclosure into an efficient, audit-ready process, trusted by Fortune 500 companies and leading consultancies.

By leveraging AI for matching business data to emissions sources and utilizing up-to-date emission conversion factor databases, Avarni automates emissions calculations with accuracy. It provides customizable dashboards aligned with disclosure standards, scenario modeling for reduction strategies, and tools for large-scale supplier engagement, thereby minimizing manual errors and enhancing transparency. The software aims to deliver compliant Scope 1-3 emissions reports significantly faster than traditional methods.