# CleanQuest

- **Event:** [Meta Global AI Developer Hackathon](https://cerebralvalley.ai/e/meta-ai-developer-hackathon)
- **When:** Oct 26, 12:00 PM – Nov 4, 9:00 PM (EST)
- **Where:** Online
- **Team:** [Ernesto Rodriguez](https://cerebralvalley.ai/u/oBEATS)
- **GitHub:** https://github.com/officebeats/cleanquest
- **Demo video:** https://www.youtube.com/watch?v=MQ7P3IyOubo
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/4858

THE PROBLEM
Commercial cleaning employs 2.4 million individual cleaners in the U.S. CleanQuest uses AI to gamify validating that work: clean, time, technique. Crews see where better products and better training make them more efficient and productive.
- Most crews get the bare minimum: minimal feedback, recognition, or proof of work.
- Companies lose accounts over "they didn't clean" disputes they cannot settle.

HOW IT WORKS — AI AT EVERY STEP
1. Check in: pick a language (English, Spanish, Polish), tap dropdowns — site, sector, area, spot. Zero typing.
  - Consent reads aloud: faces never identified; scores never used for discipline.
  - The before photo is captured in-app. No gallery uploads.
  - On-device MediaPipe (EfficientDet-Lite) rejects wrong-room and person-in-photo shots on the spot.
2. Run: a locked 90-second timer — "Quality first. Time second."
  - A neural host hypes the cleaner every 6–8 seconds, in their language. Encouragement only, never coaching.
  - 715 pre-rendered neural clips (Kokoro-82M + native ES/PL voices) ship in-app; host works offline.
  - One tap on COMPLETE CHALLENGE captures the after photo.
3. Get scored by Muse Spark Open (Meta open weights), run on hackathon partner credits:
  - Baseten ($100 credits + 2M TPM) serves the model; Fireworks AI ($100 credits) fails over, via a serverless proxy. Zero user keys.
  - Meta Model API credits ($150) funded Muse Spark 1.3 + Muse Wonder usage during the build.
  - The model grades every surface in the photo pair: clean, partly clean, missed.
  - It counts objects cleared vs. objects remaining; the app weights the verdict:
    - Clean 50% · Technique 25% · Time 25% (the timer supplies Time).
  - SAM 3.1 segmentation (own key) or Muse box_2d outlines each surface on their photos.
  - The system scores. Nobody can edit a score.
  - Settings proves it live: run log + telemetry test, verified on both providers (98% - 1,405 tokens; 96% - 1,695 tokens).
  - Optional own key unlocks Muse Spark 1.3 scoring and Muse Voice Transcribe.
  - Can't judge fairly? NOT SCORED + one plain reason (too dark, glare, camera moved) + a retake button.
4. Train and compete:
  - Daily Deck: tap-through training cards, AGREE / DISAGREE, day streaks.
  - Dual leaderboards: Shift Challenge + Daily Deck (Quality / Time / Style).
  - Personal bests, streaks, a 13-week consistency meter, a breakroom spectator board.
  - A built-in Judge Demo replays a sample run: 93%, S-Rank, in seconds.

HOW IT MAKES MONEY
- Free for cleaners, forever. Sponsors fund the game.
- The market: ~$100B U.S. commercial cleaning revenue, 63,000+ firms.
- Brands pay $15K-$55K per package to reach crews via shows and associations.
- Associations and brands sponsor by category: one per category.
- Companies pay to use an earned credential commercially, never to earn it.
- Money never touches scoring: no say over scores, training answers, or rankings.

## More from Meta Global AI Developer Hackathon

- [Lente](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/4855)
- [Funhouse](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/4856)
- [LifeLens](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/4857)
- [LENHROS](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/4859)
- [Codekrafters](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/4860)
- [Cortivra](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/4861)

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