Hack@Brown 2026 | Jan 31 – Feb 1
Built by TEAM CMYK: Candy Xie, Michael Rostom, Yolanda Hu, Karen Yang
NOTICE: This project was developed with significant assistance from AI tools. Please be aware that the code may contain security vulnerabilities or unexpected errors.
Location Intelligence Platform
AI-powered multi-agent platform that transforms "I want to open a business" into a complete location intelligence report — with market analysis, revenue projections, competitor gaps, and demographic heatmaps.
vantage.mp4
Site selection is the #1 factor in retail success, but:
- Enterprise tools cost $10K–$50K+/year
- Small business owners are priced out
- 70% of consumers say location influences their decision to visit
- Wrong location = business death
Vantage is a multi-agent system that finds the best location using
- Location Analysis — Scored recommendations with confidence levels
- Competitor Intelligence — Live data from Google Places with gap analysis
- Revenue Projections — Conservative/Expected/Optimistic scenarios
- Demographic Heatmaps — Population density, income, and age distribution overlays
┌─────────────────────────────────────────────────────────────┐
│ USER INPUT │
│ "Boba shop in NYC, targeting students, $8.5K rent budget" │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ FLASK HTTP BRIDGE │
│ • Dispatches to specialist agents │
└─────────────────────────────────────────────────────────────┘
│
┌───────────────────┼───────────────────┐
▼ ▼ ▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ AGENT 2: │ │ AGENT 3: │ │ AGENT 4: │
│ LOCATION SCOUT │ │ COMPETITOR │ │ REVENUE │
│ │ │ INTELlIGENCE │ │ ANALYST │
│• Foot Traffic │ │ • Google Places │ │ • Revenue calc |
│• Transit data │ │ • Foot Traffic │ | • Break-even │
│• Demographics │ │ • Saturation │ | • Projections │
│• Transit data │ │ │ │ |
│ │ | │ | |
└─────────────────┘ └─────────────────┘ └─────────────────┘
│ │ │
└───────────────────┼───────────────────┘
▼
┌─────────────────────────────────────────────────────────────┐
│ FLASK HTTP BRIDGE │
│ • Aggregates agent responses │
│ • Transforms data for frontend │
│ • Serves location results with metrics │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ REACT FRONTEND + GOOGLE MAPS │
│ • Interactive map with heatmap overlays │
│ • Location scoring dashboard │
│ • PDF report generation │
│ • Real-time comparison view │
└─────────────────────────────────────────────────────────────┘
╔═══════════════════════════════════════════════════════════════╗
║ EXAMPLE OUTPUT REPORT ║
╠═══════════════════════════════════════════════════════════════╣
║ #1 RECOMMENDATION: EAST VILLAGE ║
║ Overall Score: 92/100 | Confidence: HIGH ║
║ ║
║ SCORE BREAKDOWN ║
║ ├─ Foot Traffic: 88/100 (HIGH confidence) ║
║ ├─ Transit Access: 95/100 (HIGH confidence) ║
║ └─ Competition Gap: 79/100 (MEDIUM confidence) ║
║ ║
║ REVENUE PROJECTION ║
║ Conservative: $28,500/mo | Moderate: $42,200/mo ║
║ Optimistic: $58,800/mo | Break-even: 6 months ║
║ ║
║ [Download PDF] [Compare Locations] [View Map] ║
╚═══════════════════════════════════════════════════════════════╝
- Google Places API — Live competitor data (ratings, reviews, hours)
- RentCast API — Rent price estimates
- Visa Merchant Search API — Merchant spending insights (sandbox)
- Bi-Annual_Pedestrian_Counts: NYC Open Data
- Business_licenses: NYC Open Data
- Demographics: NYU Furman Center’s CoreData.nyc
- Storefronts_Vacant_or_Not: NYC Open Data
- Subway_stations: NYC Open Data
python backend/http_server.pyThe backend server will run on http://localhost:8020
# Navigate to frontend directory
npm install
npm run devThe frontend will run on http://localhost:5173
- VITE_GOOGLE_MAPS_API_KEY. Turn on Maps JavaScript API, Maps Embed API, Street View Static API
- VITE_RENTCAST_API_KEY
- VITE_OPENAI_API_KEY
- GEMINI_API_KEY
- GOOGLE_PLACES_API_KEY
- NYC_TOKEN
- RENTCAST_KEY
Submit a location analysis request.
Query Parameters:
type(string): Business type (e.g., "Boba Tea Shop", "coffee shop", "bakery")demo(string): Target demographic (e.g., "students", "professionals", "families")budget(number): Monthly rent budget
Response:
{
"status": "ok",
"results": [
{
"request": {
"business_type": "Boba Tea Shop",
"target_demo": "students",
"rent_estimate": 8500
},
"overall_score": 87,
"location": {
"name": "Location Name",
"address": "123 Main St",
"coordinates": {...}
},
"metrics": [...],
"competitors": [...],
"revenue": [...]
}
],
"total_count": 1,
}