Revolutionizing ESG through AI

Stemming from cutting-edge research, we are developing a ground breaking paradigm for ESG through technologies of the future


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The Problem

Environmental, Social, Governance (ESG) is an emerging field for enhancing business sustainability. However, ESG scores are qualitatively determined, leading to divergent and arbitrary ratings:
  • Companies: Inconsistent ratings limit effective sustainability guidance for companies, hindering their ability to identify and improve upon ESG weak-points
  • Investors: Investors fail to systematically identify sustainable companies, limiting available capital for greener long-term ventures
  • Consumers: Consumers fail to identify the sustainability considerations hidden to the naked eye, causing them to buy products from companies they may not support

Our Research-Based Solution

We are scaling our academic research from MIT to make data-driven ESG insights more accessible to companies:
  • Data: We leverage data from social networks (i.e., X, Glassdoor, LinkedIn) and sustainability reports to provide a holistic company analysis
  • Machine Learning: Our system integrates an ensemble of machine learning techniques to identify sustainability trends between peer businesses and industries
  • Natural Language Processing: We implement cutting-edge NLP algorithms through Large Language Models (LLM) and Bidirectional Encoder Representations from Transformers (BERT) to provide clear insights

Products

ESG Glass AI is rolling out a suite of products to enhance ESG materiality navigation

Social Network

This research leverages social networks such as Twitter, LinkedIn, Google News, and more, to provide outsider perspectives on ESG topics. Calibrated to the SASB Materiality sectors, this product ensures alignment with sector-based sustainability goals. In addition to providing insight into social network ESG sentiment.

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Sustainability Reports

This project analyzes corporate sustainability reports to parse key performance indicators (KPIs) that indicate quantitative impact. This can facilitate the rating process while also helping investors navigate through problems of greenwashing. Finally, our custom filter allows for quantitative screening of companies based on criteria.

Coming Soon...

Meet the Founder

Aarav Patel, Founder & CEO

Ever since joining MIT’s Center for Collective Intelligence, Aarav has eagerly been applying his quantitative skills to address ESG divergence. Aarav has actively engaged in the ESG space through research, competition, and internship. He looks forward to applying new technology through machine learning, NLP, and AI to improve business sustainability.

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