Inspiration
Our inspiration came from the growing gap we saw in the AI community, between those who can build with AI and those who can’t. As the AI revolution accelerates, we’ve noticed that people without a technical background are often left behind, even when they have valuable expertise in areas like climate and sustainability. In this new era, non-technical experts seem to have lost their leading voice, yet they hold the real-world insights that technology alone can’t replace. We built SunnySett to change that: to help them not only use AI, but also lead with it, combining their knowledge with AI to drive meaningful progress in climate and sustainability.
What it does
SunnySett is a no-code AI hub that makes complex AI workflows simple, modular, and accessible to everyone. It connects users to open-source models and datasets, allowing them to discover, run, and deploy AI solutions in just a few clicks. Through our Climate Hub, SunnySett enables individuals in climate and sustainability fields to easily apply AI/ML models to the datasets, then generate forecasting, energy optimization, and environmental insights, without requiring them to write a single line of code.
How we built it
We built SunnySett using Python, React, and FastAPI. The backend integrates models and datasets through Hugging Face, GitHub, and Kaggle APIs. We used Google Cloud Functions and BigQuery for data processing and PostgreSQL for storing project data. Lovable AI helped us quickly prototype and refine our user interface We also combine no-code simplicity with advanced tools like a chatbot assistant and live code bar for interactive model customization.
Challenges we ran into
As we explored integrating more advanced AI agents and complex workflows, each with different APIs, dependencies, and runtime requirements, it quickly became messy. It's really hard to do one-click deployment. We also struggled to simplify a product that offers many features; finding the right balance between accessibility and flexibility took multiple iterations and design refinements.
Accomplishments that we're proud of
During this hackathon, we built a fully functional version of SunnySett, a working web platform that automates model discovery and deployment. Within a few days, we connected the platform to 13 open-source climate and sustainability datasets and integrated around 10 pre-trained models capable of supporting forecasting and environmental analysis. Our prototype allows users to search, run, and compare these models directly in one workspace, no setup required.
What we learned
Through this hackathon, we learned that making AI easy to use is not just a technical problem; it’s also about people. It’s more than just connecting models or datasets; it’s about creating a simple and friendly way for anyone to use AI, no matter their background. We also learned that bringing together different AI agents and climate datasets is harder than we thought, and it takes many rounds of testing to make the system both powerful and easy to use.
What's next for SunnySett
Next, we want to grow SunnySett by adding more climate and sustainability models and datasets — tools that help people predict weather, optimize renewable energy, and study environmental change. We’ll keep improving our chatbot assistant and live coding bar to make model customization even smoother. Beyond the product, we’ll build a community where climate and AI enthusiasts can share projects, datasets, and feedback with each other. Finally, we’ll create learning materials to help non-technical users learn how to apply AI to their own climate projects, giving them the confidence to make data-driven decisions for a more sustainable future.
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