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Case Study · Mexico Vertical SaaS

FloraFlow

AI Floriculture Revenue Optimizer

Estado de México produces roughly 70% of Mexico's cut flowers, and most growers still grade by hand, price by gut, and ship blind. FloraFlow gives them a production-grade revenue stack: computer-vision photo grading, 30-day demand forecasting, 7-day dynamic pricing, satellite-based crop health monitoring, and a real-time bilingual auction marketplace with AI-floor pricing — built specifically for the Cuemanco / Jamaica wholesale corridor.

39

API Endpoints

30 days

Demand Window

7 days

Pricing Window

ES / EN

Languages

Core Features

AI Photo Grading

Upload a photo of a flower batch and get an export / first / second / third grade in seconds, with confidence scores and reasoning. Cuts manual grading from hours to minutes.

Disease & Pest Detection

Spot blight, mites, and fungal infections from plant photos before they spread. Recommended interventions are tied to local distributor inventory.

Demand Forecasting

30-day demand forecast per flower type, calibrated against CDMX wholesale market data and seasonal events (Día de las Madres, Día de los Muertos, etc.).

Dynamic Pricing

7-day rolling price recommendations that account for supply, demand, freshness, and corridor (Mercado de Jamaica vs. Cuemanco vs. export).

Satellite Crop Health

Open-Meteo + ERA5 satellite ingestion to monitor parcel-level health, frost risk, and irrigation needs without sensors in the field.

Real-Time Auction Marketplace

Bilingual ES/EN auction marketplace with AI-floor pricing — growers post, buyers bid, the AI prevents under-pricing during oversupply windows.

Tech Stack

PythonClaude SonnetFastAPIReactTypeScriptPostgreSQL (Neon)Open-Meteo

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