Project Overview
In a world where climate data is scattered and complex, Cubet partnered with a global environmental organisation to build an AI-powered platform that allows users to ask natural language questions and receive precise, explainable answers. This system unifies structured and unstructured datasets—from carbon emissions and funding records to environmental reports and ESG disclosures—and transforms them into instantly accessible intelligence for sustainability professionals and policymakers.
Industry
Environmental Tech / Climate Intelligence / GenAI for Sustainability
The Client
A prominent global environmental organisation focused on climate research, policy, and advocacy. The client supports researchers, ESG analysts, and government teams who require fast access to clean, actionable data.
Challenges Addressed
Climate stakeholders often faced challenges such as:
- Fragmented data across formats and sources like project funding logs, carbon reports, and ESG disclosures
- Complex and slow query processes that impeded responsiveness
- Technical barriers preventing non-technical teams from extracting insights
- Lack of traceability and context in data retrieval, making decisions less transparent and defensible
The organisation needed a system that combines AI‑powered language understanding, data retrieval, and explainable results—accessible to both technical and policy users.
Collaboration in Action
Cubet developed a GenAI search engine integrating LLMs, RAG, and SQL generation to allow users to ask queries in plain language. Whether exploring funding flows, emissions trends, or impact reports, the platform delivers data‑driven responses with citations and visibility into source material. Queries like “Which countries received the most climate adaptation funding in 2023?” or “Summarise environmental impact reports on coastal wind farms in the UK” are answered in seconds—with clarity, accuracy, and traceability.
Technologies Deployed
- Frontend:
- ReactJS conversational UI with visual filters
- Role-based access control for users such as internal analysts and external partners
- Backend:
- Python (FastAPI) for orchestration
- Node.js for middleware APIs
- PostgreSQL for structured datasets and MongoDB for documents
- AI & Search Layer:
- GPT‑4 with domain-focused prompt tuning
- RAG built with LangChain and FAISS vector stores
- SQL generation engine trained on ESG, climate funding, and policy schemas
- Hosted via Azure OpenAI for governance and compliance
- Integrations:
- UNFCCC APIs and CDP datasets
- Ready for integration with external ESG platforms and climate finance databases
Innovative Feature
The platform’s innovative strength lies in its conversational bridge between language and structured data. Users don’t need SQL knowledge or database access—they ask questions in natural language and receive synthesized, explainable answers. Behind the scenes, the system generates SQL queries, executes them on clean datasets, and crafts natural‑language summaries enriched with source references and traceability.
Value Delivered
- Reduced policy and research query response time from hours to seconds
- Helped internal teams easily identify funding gaps, emission trends, and overlapping projects
- Promoted cross-departmental data usage—from field teams to executives
- Surfaced high-value insights from previously siloed or underused datasets
- Improved transparency and accountability through source citations and traceability
User Feedback
Researchers and ESG professionals praised the intuitive interface and the platform’s ability to deliver complex information quickly and clearly. Policy teams found it easier to access data without technical support. Executive stakeholders valued the platform for providing defensible, traceable insights in real time.
Conclusion
Cubet’s GenAI-powered sustainability platform dramatically improved how climate data is accessed, understood, and utilised. By blending advanced AI, robust data models, and conversational interfaces, it removed technical barriers and transformed data into actionable intelligence—fueling better, faster climate decisions.
Impact Made
This solution reshaped how the client engages with climate data—making sustainability actionable and accessible. Teams across research, policy, and ESG operations now operate with real-time insight and trustworthy answers, accelerating impact and accountability in climate decision-making.