The problem FortiFi solves

The problem it solves

Financial information can move markets quickly, but users often have to make decisions based on claims, headlines, or articles that may be misleading, incomplete, or difficult to verify. Even when a claim is identified as risky, users may not have a clear way to understand how that risk could affect their ETH holdings or what protection options are available.

FortiFi addresses this by combining multi-model AI verification with evidence gathering, portfolio risk assessment, and live options protection. It helps users evaluate financial claims before acting, understand potential downside exposure, and discover suitable ETH protection strategies through Thetanuts. The system also provides an auditable record of its analysis and completed protection actions through Sui, making the decision-making process more transparent and verifiable.

Challenges we ran into

Challenges we ran into

One of our biggest challenges was our team's background. We are all cybersecurity students rather than software engineering students, and most of us had limited experience building a complete application involving AI, blockchain, frontend, backend, and smart-contract integrations.

This was also the first or second hackathon for everyone on the team, so we had to learn how to work with unfamiliar technologies while developing the product under a strict time constraint. Integrating multiple external technologies such as Gonka, Thetanuts, Base, and Sui required us to understand APIs, wallet interactions, blockchain transactions, and different development environments simultaneously.

Testing the blockchain components presented another practical challenge. We did not have sufficient funds in our wallets to freely test every on-chain operation, particularly automated contract interactions on Sui. As a result, we had to be careful with testing and work within the available testnet resources while ensuring that the core functionality could still be demonstrated.

Despite these limitations, the challenges forced us to simplify our architecture, divide responsibilities across the team, and focus on delivering a working end-to-end prototype rather than attempting to build every feature to production scale.