EcoFin AI – Intelligent Sustainability Finance Evaluator

Inspiration

Access to finance remains one of the biggest barriers for sustainable projects. Many green initiatives with real environmental and social impact struggle to secure funding due to complex evaluation processes, lack of transparency, and inconsistent decision-making. We were inspired to bridge this gap by using AI agents to make sustainability finance more accessible, data-driven, and fair—ensuring that impactful projects get the funding they deserve.

What it does

EcoFin AI is an intelligent sustainability finance evaluator that analyzes green projects in seconds. Users input project details such as environmental impact, financial feasibility, risk level, and SDG alignment. The platform then generates: A sustainability score,Risk assessment,Impact analysis ,Smart financing recommendations This enables faster, more informed decisions for investors, institutions, and policymakers.

How we built it

We built EcoFin AI using:

Python for backend logic

Streamlit for an interactive and intuitive web interface

AI-based scoring logic to evaluate sustainability, financial risk, and impact

Data visualization to clearly present insights and recommendations

The system is designed to be modular, scalable, and easy to extend with advanced AI models in the future.

Challenges we ran into

One of the main challenges was balancing simplicity with meaningful analysis. Designing a scoring system that is transparent, explainable, and aligned with sustainability standards required multiple iterations. We also faced technical challenges while integrating Streamlit, managing dependencies, and ensuring the application ran smoothly across different environments.

Accomplishments that we're proud of

Successfully built a working AI-powered prototype within the hackathon timeline

Created a clean, user-friendly dashboard for sustainability evaluation

Aligned our solution closely with the theme “AI Agents Unlock Finance for Sustainability”

Demonstrated how AI can drive real-world financial impact for sustainability

What we learned

Through this project, we learned how AI agents can support smarter financial decisions while maintaining transparency and trust. We gained hands-on experience with rapid prototyping, UI development using Streamlit, and designing systems with social and environmental impact in mind.