Feature Analyzer — seven sources, one view
A centralized platform that replaced scattered manual analyses with a real-time dashboard — weaving seven heterogeneous data sources into one pipeline teams rely on daily.
The problem
Feature analysis at scale was fragmented. Data lived in seven heterogeneous sources, and teams ran manual, one-off analyses with no single real-time view of what was happening across the pipeline.
The gap wasn't data — it was correlation. People needed to collect, analyze, and report in one flow, not seven separate tabs.
The pipeline
The platform follows a clear chain: heterogeneous sources feed a FastAPI backend that collects, analyzes, and correlates data — then a React dashboard surfaces real-time insights and structured reports.
What I built
Creator and lead developer. I designed and shipped the full stack — FastAPI services for the data pipeline, a React dashboard for real-time visibility, and the workflows that teams adopted as their daily reference.
AI adoption angle
Building at Nokia accelerated my AI-native workflow — the same Cursor-and-agents approach I later scaled across teams with internal portals and demos. Shipping this dashboard taught me how to move fast in enterprise constraints without sacrificing rigor.
Dashboard previews
Internal tooling — no public URL. The interface prioritizes density, clarity, and real-time signal over polish for demos.
Want the full story?
The Nokia chapter is where production craft met AI adoption — read the full story from internship to the person teams call to move faster.