QuickBite

Overview

QuickBite is a group decision-making app designed to solve one of life's most frustrating micro-debates: "Where should we eat?" Whether you're out with friends, planning a family dinner, or organizing team lunch, the endless back-and-forth of "I don't know, what do you want?" can waste 30+ minutes of everyone's time.

With QuickBite, the process takes less than 2 minutes. The host creates a session by choosing a location and setting preferences (cuisine types, dietary restrictions, search radius). QuickBite then curates 10 restaurant candidates using Google Places and Yelp data, filtered intelligently by cuisine, open hours, distance, and dietary needs. Each participant votes on all 10 restaurants with a simple three-option system: Yes (strong preference), Maybe (acceptable), or No (rather not). No lengthy deliberation—just quick, honest preferences.

Once everyone votes, QuickBite instantly calculates a fair winner using a transparent scoring algorithm. The system considers vote preferences, distance penalties, price matching, and open hours to find the restaurant that best satisfies the whole group. Results show the top 3 options with detailed scoring breakdowns, so everyone understands why the winner was chosen. No authentication required, works on any device, and provides instant links to Google Maps for directions.

Why we built it

We've all been there: standing on a street corner with friends, or sitting in a Slack channel with coworkers, throwing out restaurant suggestions that get lukewarm responses. "How about Thai?" "Eh, I just had Thai yesterday." "Mexican?" "Too far." "That new burger place?" "Too expensive." The conversation spirals, people get hungry and cranky, and eventually someone just makes an executive decision that leaves others unsatisfied.

This isn't a technology problem—it's a coordination problem. Groups struggle to aggregate individual preferences quickly and fairly. Existing solutions are either too slow (lengthy text discussions), too random (spinning a wheel feels arbitrary), or too complicated (spreadsheets, polls with unclear methodology). We built QuickBite to provide speed, fairness, and transparency: everyone's voice counts, the math is clear, and you get from "where should we eat?" to sitting down at a table in minutes instead of half an hour.

How it works

Creating a Session: The host starts by setting a search location (current location or entered address) and configuring preferences: search radius (1-50 miles), cuisine types (30+ options like Thai, Italian, Mexican, Sushi), facility types (restaurants, cafes, food trucks, bakeries), dietary restrictions (vegetarian, vegan, gluten-free, halal, kosher, etc.), and time slot ("now" or "tonight"). QuickBite queries both Google Places and Yelp APIs in parallel to find up to 40 restaurants, then intelligently filters and scores them based on open hours, distance, cuisine matches, and dietary considerations. The system selects the best 10 candidates and stores them for the voting session.

Voting: The host shares a simple link with the group (via text, email, Slack, etc.). Participants join by entering a nickname—no signup, no authentication. Everyone votes on the same 10 restaurants using a fast card-swipe interface. For each restaurant, you see a photo, name, cuisine types, rating, distance, price level, address, phone, and hours. You choose: 👍 Yes (I'd love to go here, +2 points), 🤷 Maybe (It's fine, +1 point), or 👎 No (I'd rather not, 0 points). The whole process takes about 90 seconds per person.

Results: Once everyone completes voting (or 70% of participants finish), the system calculates the winner using a fair, transparent algorithm: base score from votes, minus distance penalties (scaled by search radius), price mismatch penalties (if the group set a budget preference), and closed-restaurant penalties. The results page shows the top 3 restaurants with full scoring breakdowns, so everyone can see why the winner was chosen. Participants can open the winner directly in Google Maps and get directions. Late joiners can still vote, and their preferences are instantly reflected in the results.

Feature highlights

• Location-based Discovery: Use your current location or enter any address to find nearby restaurants within 1-50 miles
• Smart Filtering: 30+ cuisine types, 8 facility types (restaurants, cafes, food trucks, etc.), 10 dietary restriction tags, and time-slot optimization ("now" vs "tonight")
• Dual-Source Data: Combines Google Places and Yelp to maximize restaurant coverage and data quality
• Hours-Aware: Automatically filters out closed restaurants and those closing soon; includes places opening within 30 minutes
• Fast Group Voting: No authentication required—just enter a nickname and start voting in seconds
• Three-Option Voting: 👍 Yes (+2), 🤷 Maybe (+1), 👎 No (0) for quick, intuitive preference expression
• Fair Consensus Algorithm: Transparent scoring with distance penalties, price matching, and detailed breakdowns so everyone sees why the winner was chosen
• Mobile-Responsive: Works seamlessly on phones, tablets, and desktops with touch-optimized voting interface
• Instant Results: Top 3 ranked restaurants with scoring explanations and direct Google Maps integration
• Real-Time Participation: See who's joined, who's voting, and who's completed in real-time
• Zero Friction: No app downloads, no signups, no passwords—just share a link and go

Notes

• Current Status: Web prototype actively used internally; next phase includes Google/Apple sign-in, saved groups, two-round cuisine voting, and session timers
• Tech Stack: Built with Next.js 14, TypeScript, React, Tailwind CSS, PostgreSQL, Prisma ORM, and integrates Google Places API (New) and Yelp Fusion API
• Privacy: No long-term user accounts required; sessions are ephemeral and auto-expire after 24 hours
• For whom: Friend groups, families, coworkers, remote teams, anyone tired of the "where should we eat?" debate
• Scoring Philosophy: Transparent > Random. Every penalty and tie-breaker is explained so groups trust the outcome
• Roadmap Highlights: Auto-tally at 70% participation, better duplicate detection, host controls, re-roll alternatives, ordering integration (DoorDash/Uber Eats), optional user accounts with session history