Play 55
Supply Chain AI
Very High✅ Ready
Demand forecasting, inventory optimization, and disruption alerts.
AI-powered supply chain management platform for demand forecasting, inventory optimization, and supplier risk assessment. Combines Azure ML for time-series predictions with OpenAI for natural language scenario modeling. Features route optimization, real-time disruption alerts via Event Hubs, and what-if scenario modeling for supply chain resilience planning.
Architecture Pattern
Event-driven forecasting: ML predictions + agent-based scenario modeling
Azure Services
Azure OpenAICosmos DBEvent HubsAzure FunctionsAzure Machine Learning
DevKit (.github Agentic OS)
- agent.md — root orchestrator with builder→reviewer→tuner handoffs
- 3 agents — Supply Chain Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini)
- 3 skills — deploy (236 lines), evaluate (122 lines), tune (192 lines)
- 4 prompts — /deploy, /test, /review, /evaluate with agent routing
- .vscode/mcp.json — FrootAI MCP with OpenAI + ADX cluster inputs + envFile
TuneKit (AI Config)
- config/openai.json — scenario generation, risk analysis
- config/guardrails.json — forecast confidence, alert thresholds
- evaluation/eval.py — Forecast MAPE <15%, Alert precision >85%
Tuning Parameters
Forecast horizon daysSafety stock multiplierSupplier risk thresholdRoute optimization weightDisruption alert sensitivity
Estimated Cost
Dev/Test
$90–140/mo
Production
$3K–8K/mo