# Glyth Workplace

- **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:** [mercansey koomson](https://cerebralvalley.ai/u/Mckenzxe)
- **GitHub:** https://github.com/mercansey/glyth-workplace
- **Demo video:** https://youtu.be/ld3BNWRRQ1o?is=IlYFt9s5T1YrRg6d
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3383

Glyth Workplace is a privacy-preserving personal intelligence system designed to improve how individuals and organisations respond to changing workload, capacity and daily context.

Most workplace software measures what has already happened. Glyth is designed to understand what is changing now, help the individual adapt, and give organisations privacy-safe signals they can act on before pressure becomes a larger problem.

For employees, Glyth maintains persistent personal context across work patterns, health signals, commitments, goals and routines. When something meaningful changes, it can adapt the user’s day.

For example, if someone sleeps 4h42 after a high training-load day and has an important meeting at 14:00, Glyth can reduce training demand, protect deep-work time, introduce recovery time and defer lower-priority work while preserving fixed commitments.

Meta’s API acts as the reasoning and interpretation layer. Glyth compiles only the relevant context into structured requests, Meta produces validated reasoning and recommendations, and deterministic application logic controls calculations, constraints, permissions and execution.

The employee experience includes adaptive modules such as Mindfulness, Fitness, Finance and Family. These are not separate AI applications. They are intervention surfaces connected to the same context and orchestration system.

The workplace layer then converts a strictly limited set of consented work-pattern signals into privacy-preserving organisational intelligence.

Employers never receive individual sleep, recovery, health, financial, family, private-message or personal-context data. Workplace data is aggregated behind consent controls, category allowlists and a minimum cohort threshold before it can enter employer reasoning.

The employer dashboard highlights organisational patterns such as workload pressure, meeting density and focus fragmentation, then recommends bounded interventions such as protecting focus windows or reducing unnecessary meeting load.

This creates one closed loop:

Employee context → adaptive action → privacy-safe workplace aggregate → organisational insight → intervention → outcome.

Glyth Workplace was built from scratch during the hackathon to explore how Meta-powered personal intelligence could support both employees and organisations without turning personal context into employee surveillance.

## More from Meta Global AI Developer Hackathon

- [OvO](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3380)
- [Alibi](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3381)
- [Manuel](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3382)
- [BoardDream](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3384)
- [ELYND](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3385)
- [SeeForMe](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/3386)

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