StorePulse AI
A dashboard for store owners to track sales, orders, customers and inventory, then use AI to create practical business and product content.
Engineering decisions behind StorePulse AI.
Interfaces, application logic and production experience move together—not as isolated layers.
What I worked on.
Designed and built the authenticated product experience, analytics views, Supabase data workflows and Gemini-powered content tools.
The result is a working SaaS product that brings authentication, store data, analytics and AI tools into one dashboard.
What the project includes.
- Supabase authentication and protected routes
- Revenue, order, customer and inventory analytics
- Searchable product, order and customer workflows
- AI business insights and product-content generation
- Saved AI output history and store settings
- Responsive interface with dark mode
How the work was approached.
- 01
Kept analytics tied to persisted store records instead of static dashboard data.
- 02
Separated AI generation from saved output history so useful results remain reusable.
- 03
Built responsive tables and filters for operational use beyond presentation-only charts.
Technology used on this project.
The stack below reflects the tools and platform involved in my contribution—not a generic list of everything I know.
Next.js
TypeScript
Tailwind CSS
Supabase