Landed

Landing Page
Personalized Plan
AI Agent Helper
Suggested Roadmap
Credit Card Matching

Inspiration

Landed was inspired by the unique challenges faced by first-year college students, particularly young women, who are often navigating financial independence, career decisions, and money management for the first time. As the first generation students, we found that traditional ways of getting credit lack tailored guidance, leading to missed opportunities for long-term success. We wanted to create a tool that empowers them with accessible, AI-driven support to build financial confidence and connect it to their broader goals.

What it does

Landed helps first-year college students, especially women, create personalized credit plans. Users answer 15 questions about their credit, income, and goals to receive real-time recommendations on credit cards, approval odds, budgeting strategies, earning tips, investing basics, and career-related financial advice—all in under 2 minutes. It uses technology to deliver no-jargon, actionable insights, making it inclusive for those underserved by traditional tools.

How we built it

We developed Landed using Node.js for the backend, integrating SQLite for multi-user data storage with tracked history. The AI component leverages machine learning models to analyze user inputs and generate personalized plans. The frontend is built with React for an intuitive, mobile-friendly interface. We incorporated secure authentication and real-time data syncing to ensure a seamless digital experience.

Challenges we ran into

Integrating AI for accurate, jargon-free recommendations proved complex, as we had to balance personalization with data privacy. Ensuring the app felt empowering and accessible to Gen-Z women required extensive user testing to avoid alienating language. Scaling the database for multi-user history tracking while maintaining performance was another hurdle, especially with real-time updates.

Accomplishments that we're proud of

We're proud of our thorough market research before implementation, where we talked to over 10 Fidelity professionals to gain valuable advice and perspective on our product. This informed our development, leading to a fully functional prototype that provides personalized credit plans in under 2 minutes. The app's focus on inclusivity has resonated, helping students who felt left behind by other financial tools. We've also successfully implemented a robust history-tracking system for data persistence across multiple users.

What we learned

We learned the importance of user-centric design in financial tech, especially for underrepresented groups like young women. AI integration requires careful ethical considerations to avoid bias, and iterative feedback loops are crucial for refining accessibility. Building with persistence in mind taught us about scalable database architectures for collaborative features.

What's next for Landed

Next, we'll focus on improved onboarding with more user-specific questions that tie deeper into the user’s personal roadmap for better personalization. We'll enhance security by implementing two-factor authentication via email or phone. Additionally, we'll add tax advice features offering personalized guidance on approaching the tax filing process. Further plans include gamified elements for engaging money management, partnerships for real-time card approvals, multilingual support, and a community mentorship platform, with mobile app development to expand global reach.