AI Inventory SaaS Development
Budget: $750 – $1,500 USD
I’m building a cloud-based platform that helps factories and retail stores see what will sell next, trim excess stock, and automatically trigger purchase orders. The core stack so far is React for the web interface, Laravel for the backend services, and Python for the machine-learning layer, but I’m open to a developer who is stronger on either the full-stack (React + Laravel) or the AI side (Python with TensorFlow/PyTorch).
The first milestone is an MVP that delivers three headline capabilities: demand prediction, inventory optimization, and automated replenishment. Factory Managers, Store Managers, and Inventory Supervisors will each log in to a role-based dashboard that surfaces those insights in real time.
Data will flow in from ERP, POS, and e-commerce platforms, so experience building secure, scalable integrations—whether with REST, GraphQL, or webhook pipelines—is important. If you’ve worked with tools like PostgreSQL, Redis, Docker, and AWS (or similar cloud services) you’ll feel right at home.
Key deliverables
• Responsive React dashboard with auth and role-based views
• Laravel (or comparable) API service layer, documented and tested
• Python model service that ingests multi-source sales data and returns predictions via REST/JSON
• One live integration each for an ERP, POS, and e-commerce system (sandbox credentials provided)
• Deployment scripts and concise setup docs so I can spin up a staging instance in my AWS account
If you have a portfolio piece that shows similar predictive analytics or SaaS work, send it along. I’m ready to start as soon as we align on the technical approach and a sensible milestone plan.
The first milestone is an MVP that delivers three headline capabilities: demand prediction, inventory optimization, and automated replenishment. Factory Managers, Store Managers, and Inventory Supervisors will each log in to a role-based dashboard that surfaces those insights in real time.
Data will flow in from ERP, POS, and e-commerce platforms, so experience building secure, scalable integrations—whether with REST, GraphQL, or webhook pipelines—is important. If you’ve worked with tools like PostgreSQL, Redis, Docker, and AWS (or similar cloud services) you’ll feel right at home.
Key deliverables
• Responsive React dashboard with auth and role-based views
• Laravel (or comparable) API service layer, documented and tested
• Python model service that ingests multi-source sales data and returns predictions via REST/JSON
• One live integration each for an ERP, POS, and e-commerce system (sandbox credentials provided)
• Deployment scripts and concise setup docs so I can spin up a staging instance in my AWS account
If you have a portfolio piece that shows similar predictive analytics or SaaS work, send it along. I’m ready to start as soon as we align on the technical approach and a sensible milestone plan.