Content Optimization Suite

Optimization module that scores existing content against competitors and search intent, then proposes concrete edits (headings, gaps, tone, structure) right inside the editor.

Build something similar

Built under NDA

Screens, code, and the client's name aren't public. The architecture and my role are described below; happy to walk through details on a call.

Role: Full-stack developer
Timeline: 2026
Stack: PythonFastAPIPostgreSQLNext.jsTypeScriptLLM analysisCharts

The challenge

Teams had content but no objective way to know why it underperformed. The module had to explain a score, not just show one, and turn analysis into edits a writer can accept or reject.

What I built

I implemented multi-axis scoring (coverage, structure, tone, intent match) computed by an analysis pipeline, visualized with radar and heatmap views, and surfaced as inline suggestions in the editor. Every suggestion carries its reasoning so writers keep control. Details and client are under NDA.

Key features

Multi-axis scoring with explanations
Competitor gap analysis
Inline, accept/reject suggestions in the editor
Radar and heatmap visualizations, exportable to reports