Leading SaaS Based ESG Risk & Due Diligence Software

jidabyte helps build advanced data analytics using LLMs for extraction, analysis, and NLP.

Overview

A leading SaaS platform that helps businesses assess and manage environmental, social, and governance (ESG) risks. The software provides comprehensive tools for due diligence, enabling organizations to evaluate potential risks, ensure regulatory compliance, and make data-driven decisions to improve sustainability practices across their operations and supply chains.

Results: Data Integration and Processing Custom ESG Score Computation Transparency Promotion

Challenge

The company faced key challenges in delivering accurate and user-friendly ESG risk assessments.

  • Data Consistency & Reliability – Aggregating ESG data from multiple sources while ensuring accuracy and consistency.
  • Custom ESG Scoring – Developing specialized algorithms requiring deep expertise in data science and ESG domain knowledge.
  • User Experience – Designing intuitive interfaces to present complex ESG data in a clear and actionable way.

Solution

To address these challenges, we implemented the following solutions:

  • AI-Driven ESG Insights – Leveraged LLMs for data extraction, analysis, and NLP to derive insights from web-based ESG data.
  • Accurate ESG Scoring – Built custom Generative AI models using TensorFlow/PyTorch and collaborated with experts to develop tailored ESG score algorithms.
  • Scalable & User-Friendly Platform – Deployed on AWS for scalability and cost-effectiveness, while designing intuitive interfaces through user research and testing.

Outcome

  • Comprehensive ESG Insights – Provided users with detailed ESG data, including scores, asset details, and disclosure reports for in-depth analysis.
  • Informed Decision-Making – Enabled stakeholders to make data-driven investment decisions aligned with sustainability goals.
  • Enhanced Transparency – Fostered trust and drove positive corporate sustainability changes through a transparent ESG Information Platform.