AI Supply Chain

📦 AI Supply Chain Subnet — Subnet #6 | Bittensor Ideathon Pitch

Supply chain disruptions cost the global economy $184B+ per year. AI Supply Chain Subnet is a Bittensor subnet that creates a competitive marketplace where AI models compete to deliver the most accurate logistics predictions — scored against real shipment data, rewarded with $TAO.

📌 The Problem:

* Supply chain disruptions cost $184B+ annually worldwide

* Existing tracking systems are reactive, not predictive

* IoT and logistics data is siloed across carriers and platforms

* Small businesses lack access to enterprise-grade analytics

💡 Our Solution:

A Bittensor subnet where miners build AI models for ETA prediction, disruption risk scoring, and demand forecasting. Validators verify predictions against actual delivery outcomes. The best models earn $TAO rewards via Yuma Consensus.

⚙️ How It Works:

1. Validators broadcast logistics challenges (e.g., container ETA Shanghai → Rotterdam)

2. Miners run prediction models → return ETA, risk scores, and demand forecasts

3. Validators verify against actual shipment & delivery data

4. Yuma Consensus distributes $TAO to the most accurate models

📊 Miner Tasks:

* Delivery Prediction (50%) — ETA forecasting for shipments and cargo

* Disruption Risk (30%) — Supply chain disruption detection and rerouting

* Demand Forecast (20%) — 30-90 day inventory and demand prediction

🏆 Competitive Edge:

* vs Traditional Logistics → Decentralized, multi-source intelligence beats siloed systems

* vs Legacy Tracking → Predictive and forward-looking, not just GPS pings

* vs Other Subnets → Multi-modal (ETA + risk + demand) with IoT data integration

* Continuous flywheel: more rewards → better models → more accurate predictions

🗺️ Go-to-Market:

Phase 1: Testnet + logistics data provider onboarding

Phase 2: API for freight forwarders and 3PL companies

Phase 3: Enterprise integration (SAP, Oracle SCM, Flexport)

Phase 4: Global expansion — ports, customs, and cross-border logistics

🔗 Links:

GitHub: https://github.com/yt2025id-lab/bittensor-supplychain

Live Demo: See our demo video

#Bittensor #TAO #SupplyChain #AI #Logistics #DecentralizedAI #Web3 #IoT #PredictiveAnalytics #Ideathon

During the hackathon, the team successfully completed the following milestones:

• Designed the full Bittensor subnet architecture for decentralized supply chain analytics

• Built a FastAPI backend with a /track endpoint for submitting shipment tracking queries

• Developed an AI analytics engine capable of predicting disruption risk and delivery delay probability

• Implemented core data models (SupplyChainQuery & SupplyChainResponse) and database operations

• Wrote a comprehensive Subnet Proposal (SUBNET_PROPOSAL.md) covering incentive mechanism, miner/validator design, business logic, and go-to-market strategy

• Produced full technical documentation in overview.md along with pitch deck materials

• Published a clean, structured public GitHub repository ready for further development

The project is currently at the pre-seed / bootstrap stage with no external funding received to date. The team is actively pursuing grant opportunities from the Bittensor / OpenTensor Foundation ecosystem and exploring investment from VCs focused on AI Infrastructure and DePIN (Decentralized Physical Infrastructure Networks). Initial fundraising targets will be used to fund mainnet subnet deployment, IoT data pipeline integration, and engineering team expansion.