# CO

- **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:** [Zsolt Meszaros](https://cerebralvalley.ai/u/noszii)
- **GitHub:** https://github.com/nosziii/casinoos
- **Demo video:** https://youtu.be/uFieyACO8lk
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/107

**CasinoOps — AI-Powered Casino Operations Digital Twin**

Casino operations depend on tightly interconnected systems: authentication, payments, KYC, cashier services, player registration, and customer support. When one critical service degrades, failures can cascade across the entire platform. Traditional monitoring tools expose individual alerts but often leave operators to manually identify the root cause, understand the business impact, and decide how to recover.

CasinoOps transforms this process into an intelligent, verifiable incident investigation workflow.

Built during the Meta Global AI Developer Hackathon, CasinoOps combines specialized AI agents, a central reasoning system called Casino Brain, and a deterministic digital twin.

When an incident occurs, AI agents investigate infrastructure, operational, and risk signals using controlled, read-only tools. Their findings are evaluated by a mandatory deterministic verifier that checks service degradation, dependency relationships, event chronology, and evidence quality.

Only verified findings reach Casino Brain, which correlates the investigation results and helps operators understand the incident.

CasinoOps then predicts the operational and business impact of continued outages, compares mitigation strategies, and allows operators to approve a recovery simulation.

**What makes CasinoOps different:** AI reasoning is grounded in verifiable evidence, numerical predictions come from deterministic simulation rather than LLM-generated estimates, and recovery actions require explicit human approval.

The complete incident-to-recovery workflow runs in a live, interactive web application using real Meta models.

All scenarios use synthetic data. No production casino infrastructure is connected.

**Live Demo:** https://casinoops.tech

**Source Code:** https://github.com/nosziii/casinoos

## More from Meta Global AI Developer Hackathon

- [KodVani](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/104)
- [Joestar](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/105)
- [Kanopi Lens](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/106)
- [NeuroLab AI](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/108)
- [Old Forge Technologies](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/109)
- [AUTOKEREN](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/110)

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Markdown version of https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/107. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt