Supplier Intelligence Platform

A Real-Time Supplier Intelligence & Quality Monitoring Platform designed for Tesla's Electronics Supplier Industrialization team.

Overview

This platform enables real-time production performance monitoring across global suppliers, providing insights into Quality, Capacity, and Equipment performance. It uses Agentic AI for root-cause analysis and Computer Vision for automated defect detection on the edge.

Tech Stack

• Ingestion: FastAPI, gRPC, Apache Kafka
• Pipeline & Quality: Apache Airflow, Great Expectations
• Database: PostgreSQL (TimescaleDB)
• Computer Vision: Ultralytics YOLOv8, PyTorch
• AI Assistant: LangChain, OpenAI/Bedrock
• Dashboard: Streamlit, Plotly
• Infrastructure: Docker, GitHub Actions

Documentation

• System Architecture
• Data Dictionary
• Edge Deployment Guide
• API Reference

Prerequisites

• Docker and Docker Compose
• Python 3.10+
• GNU Make

Quick Start

1. Install dependencies:

   make setup

2. Start the infrastructure (Postgres + Kafka):

   make infra-up

3. Run DB migrations and seed data:

   make db-migrate
   make db-seed

4. Start Airflow pipeline:

   make airflow-up

5. Run the Ingestion API and Dashboard:

   make api
   make dashboard

6. (Optional) Run the Edge Simulator to generate traffic:

   make simulator