CAPSTONE

IronicTuning

My Computer Science capstone: a full-stack automotive platform combining a product catalog, user accounts, news aggregation, and an AI assistant.

Connecting an application’s moving parts

IronicTuning brought several web-development concerns together in one automotive platform: account access, catalog data, carts and orders, administrative views, external news content, and an AI assistant. The capstone gave me a way to work across the interface, backend, and relational data model.

The relational models connect users with the records they create or manage. Role-based administration separates management tasks from ordinary browsing, while RSS ingestion supplies automotive news. The move from SQLite to PostgreSQL and the use of migrations form part of the application’s development history.

My contribution

I designed the application and relational models for users, products, orders, carts, and page views. I added role-based administration, automotive RSS ingestion, and an OpenAI-powered chatbot.

The output

A capstone application originally deployed on Render, with administrative analytics and a migration from SQLite to PostgreSQL. Manual workflow testing covered accounts, product management, and cart behavior.

IronicTuning admin dashboard with user, product, news, analytics, and order management links.
The original administrative dashboard organizes user, product, news, analytics, and order management. This local rendering uses a sample account.

Inside the capstone

Read the dashboard as a map of the management workflow, then follow the architecture diagram to see how the interface, Flask backend, database, and external services fit together. These are saved project visuals. The dashboard uses a sample account, and its controls are not a live admin session on this portfolio.

Original architecture diagram connecting the frontend, Flask backend, PostgreSQL database, AI service, RSS ingestion, and administration.
The capstone architecture connects the frontend, Flask backend, PostgreSQL database, and external AI and RSS services. Open the diagram to inspect the component labels.
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