BonsAI is a scalable, AWS-hosted ESG compliance platform that uses LLM, RAG, and secure integrations to collect and analyze data across eight ESG taxonomies through flexible, API-driven methods.
The Challenge · The Challenge · The Challenge
Develop a comprehensive system that integrates multiple data sources and provides analysis of ESG (Environmental, Social, and Governance) data, facilitating compliance with regulatory reporting requirements and supporting the UK’s commitment to sustainable practices in agriculture and logistics.
The system aims to empower users to make sense of their own data, demystify ESG compliance requirements, and simplify government regulatory reporting.
Solution
A flexible ESG compliance system that supports multiple data collection methods—such as checklists, certifications, questionnaires, internal calculations, and third-party integrations—and adapts its methodology annually. It uses LLM and RAG to analyze submitted documents against a repository of UK ESG requirements, international standards, and proprietary calculations across eight ESG taxonomies, including regulatory compliance, economic dependencies, food trade impact, supply chain traceability, carbon emissions, water and waste management, and biodiversity health.
Build
- API-driven architecture using Fastify-based REST API backend
- Frontend built with Next.js and TypeScript
- Hosted on AWS infrastructure for scalability and reliability
- Utilizes AWS services: Cognito (authentication), S3 (storage), and SES (email)
- PostgreSQL database for structured data management
- Secure integrations with 9AI and Farm Carbon Toolkit
- Fully deployed on AWS for robust performance and infrastructure consistency
INTEGRATION
AI Engine
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Farm Carbon Toolkit
AI generates code for repetitive tasks, saving time and effort.
Our Approach
The process started with an analysis of the current UK ESG compliance requirements and a prototype of the data collection system ensuring the capacity of multiple data gathering methods. An agile development framework was used with 2 week sprints focusing on each ESG taxonomy, data gathering methodology, and user navigation and controls. This provides usable and presentable core functionalities every 2 weeks that allow for quick feedback and user experience analysis.
A focused system analyst and designer provided the necessary information and assets prior to developer needs as well as documentation of the functional flows of the system and UI experience.
TECH STACK
- Backend: Node JS and Fastify
- Frontend: Next and TypeScript
- AI: Phyton/Flask and Langgraph
Similar Studies
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