Granted

Granted.

Inspiration

Nonprofit organisations often struggle to find relevant grants despite the abundance of funding opportunities available. Existing portals, including OurSG Grants, present information in dense lists with rigid filters, forcing users to manually sift through large volumes of content. This creates cognitive overload, missed opportunities, and inefficient grant discovery. We were inspired to rethink grant discovery through a more human-centric, intuitive, and engaging experience (prior experience from dating apps), one that mirrors how people naturally make decisions today.

What it does

Granted is a grant discovery platform that helps nonprofits find, evaluate, and track funding opportunities effortlessly.

Using a swipe-based interface, nonprofits can quickly indicate interest or disinterest in grants. An AI match score highlights how well each grant aligns with the organisation’s profile, needs, and priorities. Users can also browse all grants in a structured view, apply advanced filters (issue area, scope, funding amount, agency, deadlines), and save grants into a dedicated dashboard for tracking and follow-up.

How we built it

Granted was built using a Next.js + React frontend for a fast, responsive, and mobile-friendly experience. The swipe interface, saving mechanism, and filtering system were designed to be intuitive and frictionless.

On the backend, we used Python and Firebase Firestore to store structured grant data scraped from public sources. Grants are ingested from JSON/JSONL files and normalized before being stored. AI-powered match scoring and filtering logic are handled server-side, enabling dynamic ranking and personalized discovery. Real-time data syncing ensures saved grants and filters update instantly.

Challenges we ran into

Designing a swipe-based interaction that feels natural for professional use cases without trivializing the grant process
Working around Firestore’s query limitations, which required thoughtful client-side filtering for complex multi-criteria searches
Structuring highly unstandardized grant data into a clean, queryable schema
Balancing speed, usability, and clarity within a short hackathon timeline

Accomplishments that we're proud of

Successfully transforming a traditionally complex grant portal into a fast, engaging, and intuitive experience
Implementing a functional swipe + save + filter system within a short build window
Designing a scalable data ingestion pipeline for real-world grant data
Creating a platform that is immediately usable and impactful for nonprofits

What we learned

This project reinforced the importance of human-centered design, especially when working with complex, information-heavy systems. We learned how interaction patterns commonly associated with consumer apps can be thoughtfully adapted for professional and social-impact contexts. Technically, we gained deeper experience working with Firestore data modeling, client-side filtering strategies, and integrating AI-driven ranking into real applications.