Solo Project

MindSafe

AI-powered Chrome extension for evaluating children's videos through a child-development lens.

MindSafe evaluates children's videos based on pacing, language, emotional content, and behavior modeling, generating a Development Score and Brainrot Index to help parents choose healthier content.

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MindSafe
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My Role

I built MindSafe independently, focusing on the extension concept, analysis pipeline, backend processing, model-assisted scoring, and parent-facing product experience.

  • Designed the evaluation approach around pacing, language, emotional content, and behavior modeling
  • Built backend processing with Python and Flask to support video analysis workflows
  • Used audio and language processing techniques to extract signals from children's video content
  • Created scoring logic for the Development Score and Brainrot Index
  • Packaged the project as a browser-extension experience for parent-focused content review
Problem

Parents do not always have enough context to judge whether a video is developmentally healthy. Age ratings alone often miss pacing, overstimulation, language, and behavior-modeling concerns.

Solution

MindSafe analyzes video content through multiple signals and turns that analysis into clear scores parents can use while reviewing children's media.

Impact

The project shows how AI and signal processing can be applied to a practical safety-focused product with a clear user need.

Key Features
  • Chrome extension workflow for reviewing children's videos
  • Development Score for parent-friendly content evaluation
  • Brainrot Index for identifying overstimulation risk
  • Audio signal processing for pacing and media analysis
  • NLP-assisted review of language and content signals
Tech Stack
  • Python
  • Flask
  • Whisper
  • NLP
  • librosa
  • Chrome Extension
  • Audio Processing