TurtleRecall

Inspiration

A student's zip code, income, or first-gen status shouldn't determine whether they find the right scholarship, make it to class on time, or feel safe walking home at night. But at UMD, the systems that are supposed to help students are broken, siloed, or just hard to find. DOTS tickets $700+ parking permits and issues 43,000+ citations a year. TerpVault-eligible students leave up to $19,700 in grants on the table. Canvas deadlines creep up while advisors are backed up. And after dark, campus navigation becomes a guessing game.

We asked: what if a suite of AI agents could fix all of this simultaneously, using real campus data, and actually be accessible to the students who need it most?

What it does

TurtleRecall is a squad of 6 purpose-built AI agents for UMD Terps, all accessible at turtlerecall.us:

• ExpediTerp surfaces the biggest campus pain points via a crowdsourced Notoriety Index, cross-referencing The Diamondback, r/UMD, SGA reports, and MPIA public records -- so the right problems get solved with real evidence.
• NavigaTerp knows every Shuttle-UM route, active detour, DOTS lot rule, and game-day caveat. Ask it where to park or which bus to catch, and it answers instantly with your exact permit type.
• NutriTerp decodes the dining hall black box -- live menus, macro matching, allergen flags, and meal swipe optimization for students with dietary restrictions.
• TerpKnight is the late-night campus companion: Blue Light locations, what's open, Nite Ride details, and safety routing after dark.
• TerpAdvisor reads your actual Canvas data, surfaces what's due, and builds a personalized study plan around your schedule.
• TerpVault matches your exact student profile against every UMD scholarship, state grant, and research stipend -- with deadlines and step-by-step application guidance. Up to $19,700 in aid most students never knew they qualified for.

The site also features an AI Lab where anyone can pick a real campus problem and generate a new agent concept on the spot, grounded in UMD's existing data infrastructure.

How we built it

The backend is Python + FastAPI, serving each agent's logic and proxying AI API calls so keys never touch the browser. The frontend is vanilla JavaScript with a terminal-inspired, data-dense UI -- built to feel like infrastructure, because that's what campus tools should feel like. Agent data is grounded in real sources: MPIA filings, The Diamondback archives, SGA public reports, and live UMD APIs. Claude and Claude Code powered the core agent logic, backend route scaffolding, and rapid iteration across the hackathon window.

Challenges we ran into

Getting agent responses to feel genuinely useful -- not generic -- required careful prompt engineering and grounding each agent in actual UMD-specific data rather than broad platitudes. The AI Lab's backend needed retry logic across model fallbacks to handle rate limits under hackathon load. Scoping 6 agents in a single hackathon timeline meant making hard calls about depth vs. breadth for each one. And building ExpediTerp's Notoriety Index required sourcing, weighting, and cross-referencing data from heterogeneous sources with very different reliability levels.

Accomplishments that we're proud of

The Notoriety Index is something we're genuinely proud of -- it's not vibes, it's a structured, source-weighted scoring system that makes campus inequities visible and legible. TerpVault targeting the $19.7K maximum grant gap is concrete and high-stakes. The AI Lab that lets anyone design the next agent feels like proof-of-concept for a living, extensible platform rather than a static demo. And we shipped a real, deployed site at a custom domain during the hackathon.

What we learned

Grounding AI in real, local data is what separates a useful agent from a chatbot. Equitable access isn't just about what you build -- it's about what data you make legible and who you design the interface for. We also learned that a clean proxy layer makes it surprisingly fast to iterate on multi-agent architectures without a heavyweight backend.

What's next for TurtleRecall

Live Canvas and UMD SIS integration for TerpAdvisor. A real-time Shuttle-UM feed for NavigaTerp using the Transit API. Voice access for TerpKnight so it's usable on the move after dark. Expanding TerpVault's database to include department-level fellowships and external scholarships targeted at first-gen and low-income students. And -- if we can get campus buy-in -- deploying ExpediTerp as an ongoing student feedback layer that actually informs university policy.

Built With

• claude
• python