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Elizabeth Stein
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Case study

experimental2025

App Idea Miner

AI-powered opportunity detection platform that collects, clusters, and analyzes "I wish there was an app..." posts. HDBSCAN clustering, sentiment analysis, and real-time monitoring.

Where wild ideas take flight and curiosity leads

Field notes

Role

Creator

Read order

Evidence first, then constraint → build → proof. Use the chapter rail to jump sections; orbit to adjacent work from the bottom of the case study.

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Source Code

Evidence

Interface & evidence

A real surface area—not a mock. Scroll the story below for constraint, build, and outcome.

Signature viewapp-idea-miner.vercel.app
App Idea Miner application interface
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Story arc

How this shipped

Where wild ideas take flight and curiosity leadsThree beats: what pressed against the work, how the stack answered, and what changed once it was live.

I · Constraint

The brief

Validating app ideas requires expensive market research. Real user needs are scattered across forums, social media, and reviews.

II · Build

The craft

Built intelligent ingestion pipeline with deduplication, NLP-powered idea extraction, VADER sentiment analysis, and HDBSCAN clustering. FastAPI backend with 21+ endpoints, React dashboard with analytics.

III · Proof

What moved after launch

Clusters similar ideas automatically with evidence links. 3.5x performance boost via Redis caching. Security hardened with WCAG 2.2 compliant frontend.

Inventory

Stack & signals

PythonFastAPIReactHDBSCANNLPRedisPostgreSQL
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Tell me what you're building

If you need someone who can own UI, systems, and AI integration without losing the plot—I'm listening. Contract, advisory, or full-time: we'll find the right shape.

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© 2026 Elizabeth Stein

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