Sire — AI-Powered Sneaker Management & Automation System
Overview
Sire is a highly advanced sneaker management and automation platform built with Django. Designed for professional resellers and high-volume operators, the system centralizes inventory, tasks, analytics, and AI-driven automation. I worked on the project as a core developer alongside a team, contributing to backend features, AI workflow integrations, dashboard development, and performance optimizations.
The Challenge
Sneaker reselling workflows involve dozens of moving parts — inventory tracking, market data, pricing decisions, bot coordination, order monitoring, and profit analysis. Existing tools were fragmented and lacked automation. Sire needed to unify everything into one intelligent platform powered by AI, handling real-time data and complex operational logic without sacrificing performance.
Project Goals
- ✔ Build a robust backend architecture using Django for complex sneaker workflows
- ✔ Integrate AI to optimize decision-making, pricing, and product monitoring
- ✔ Create automated modules for inventory syncing, task scheduling, and alerts
- ✔ Design a powerful dashboard for data-heavy analytics and resource management
- ✔ Ensure speed and scalability for thousands of queued operations
- ✔ Collaborate with a multi-developer team to deliver features rapidly
Process
Architecture & Backend Development
Contributed to the core Django backend, including designing models, building scalable APIs, optimizing queries, and maintaining overall system structure for performance and reliability.
AI Workflow Integration
Helped integrate AI modules that analyze market trends, automate pricing strategies, and trigger intelligent sneaker-related decisions such as restock predictions and profitability assessments.
Automation Features
Worked on automated tasks such as inventory syncing, stock checking, bot coordination, and alert systems to reduce manual workload and streamline reselling operations.
Dashboard & Data Visualization
Developed components for a data-rich dashboard including charts, activity logs, KPIs, and detailed analytics pages designed for high-volume sneaker operations.
Multi-Developer Collaboration
Contributed within an engineering team using Git workflows, code reviews, modular feature development, and rapid iteration cycles to maintain consistent development velocity.
Optimization & QA
Improved backend performance, reduced processing bottlenecks, optimized API response times, and ensured data accuracy across complex sneaker workflows.
Deployment & Maintenance
Assisted in deployment processes and production readiness tasks using Linux environments, ensuring system stability under real user load.
Results
- ▲ AI-powered automation reduced manual sneaker management workload significantly
- ▲ Unified dashboard improved workflow visibility for high-volume resellers
- ▲ Inventory syncing and automated processes increased operational accuracy
- ▲ Faster decision-making through real-time analytics and AI insights
- ▲ Stable production performance even with large datasets
“The engineering team delivered a powerful, intelligent platform that transformed how advanced sneaker operations are managed. Talha's contributions played a key role in building reliable automations and high-performance backend features.”
— Sire Team