cotton-intelligence-platform

byJanvi shah

I want to build this system

LandingAdmin DashboardModel RegistryBacktestTrade PositioningCrop WeatherIndia IntelligenceLoginSupply DemandMacro DriversDashboardCompeting CropsForecast
Landing

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System Requirements

System Requirement Document
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Cotton Intelligence Platform

Introduction

The Cotton Intelligence Platform is designed to provide a comprehensive, AI-driven dashboard that consolidates global market data, crop intelligence, speculative positioning, macro-economic signals, and Indian domestic data. This platform aims to support informed, data-backed cotton sourcing decisions.

System Overview

The platform ingests data from over 15 live, automated data pipelines, covering sources such as ICE futures, USDA WASDE, CFTC Commitment of Traders, Cotlook, NOAA weather, USDA NASS crop progress, ICAC, CAI India, DXY, WTI crude oil, PSF prices, and competing crop markets. It features a production-grade price forecasting model generating a 365-day daily forecast for ICE Cotton No. 2 futures (CT1).

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Functional Requirements

  • As a User, I should see all data pipelines fully automated with zero manual intervention.
  • As a User, I should have ICE CT1 daily price ingested and forecast refreshed automatically within 30 minutes.
  • As a User, I should access a 365-day daily price forecast with confidence bands.
  • As a User, I should see WASDE data auto-ingested on release day with country-wise MoM delta.
  • As a User, I should view a country-wise ending stocks panel for 7 major countries.
  • As a User, I should see Cotlook StOU displayed on a rolling 6-month window.
  • As a User, I should access a 15-day rainfall forecast by growing region.
  • As a User, I should have an India module with weekly CAI data.
  • As a User, I should see a full CFTC COT disaggregated table with 4 trader categories.
  • As a User, I should access PSF price series, Cotton/PSF ratio, and a 3-line normalized comparison chart.
  • As a User, I should see a competing crops module with USA price index and India kharif dashboard.
  • As a User, I should access a backtest module with direction accuracy and rolling MAE.
  • As a User, I should see scenario price paths for 4 time horizons.
  • As a User, I should receive pipeline failure alerts within 15 minutes of any SLA breach.
  • As a User, I should see the October–January buying window highlighted on the forecast dashboard.

User Personas

  • Admin: Manages data pipelines, oversees system performance, and handles user access.
  • User: Utilizes the platform for market analysis and decision-making in cotton procurement.
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Visuals Colors and Theme

  • layout: Ensure ample white space for a clean and elegant design, with primary green as the dominant color, reflecting the brand's logo.
  • primary: #2A9D8F
  • primary_light: #A8DADC
  • secondary: #E76F51
  • accent: #F4A261
  • highlight: #E9C46A
  • bg: #F1FAEE
  • surface: rgba(233, 245, 248, 0.8)
  • text: #264653
  • text_muted: #6D6875
  • border: rgba(38, 70, 83, 0.2)

Signature Design Concept

Interactive Cotton Market Map: The homepage features an interactive map of global cotton markets. Users can click on different regions to view detailed market data, forecasts, and trends. Hovering over regions highlights key statistics and recent changes. The map is animated with subtle transitions using framer-motion for a dynamic experience.

Interaction Model & Motion Direction

  • Interaction Model: Parallax
  • Motion Direction: Layered depth via scroll with interactive map elements and hover transitions.
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Non-Functional Requirements

  • Performance: Dashboard page load < 3 seconds. API response < 500ms.
  • Data Freshness SLAs: ICE price within 30 min of EOD settle. WASDE within 2 hours of USDA release.
  • Availability: 99.5% uptime SLA.
  • Security: HTTPS enforced, role-based access control.
  • Scalability: Backend on ECS Fargate with auto-scaling.
  • Observability: CloudWatch dashboards for all metrics.

Tech Stack

  • Frontend: React for Web
  • Backend: Python, FastAPI
  • Database: MySQL
  • AI Models: Prophet + LSTM ensemble
  • Orchestration: Docker, Kubernetes

Assumptions and Constraints

  • Access to CAI India data is confirmed.
  • PSF price data sourced from ICIS or PCI Wood Mackenzie.
  • ICE CT1 data sourced via Yahoo Finance, Barchart.com, or Investing.com.
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Glossary

  • CT1: ICE Cotton No. 2 futures
  • WASDE: World Agricultural Supply and Demand Estimates
  • CFTC: Commodity Futures Trading Commission
  • PSF: Polyester Staple Fibre
  • DXY: US Dollar Index
  • ENSO: El Niño-Southern Oscillation
Landing design preview
Landing: View Platform
Login: Sign In
Dashboard: View Overview
Crop Weather: View Planting Pace
Crop Weather: Analyze NASS Progress
Crop Weather: View Rainfall Anomaly
Crop Weather: Check ENSO Index
Supply Demand: View Production Trends
Supply Demand: Analyze Country Stocks
India Intelligence: View Pressing Data
India Intelligence: View CAI Estimate
Competing Crops: View Kharif Dashboard