# Aahwan IT Group

- **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:** [Sitesh Adhikari](https://cerebralvalley.ai/u/sitesh-adhikari)
- **GitHub:** https://github.com/sitrsh12/meta-ai-hackathon-Aahwan_IT_Group
- **Demo video:** https://www.youtube.com/watch?v=JlpBn9pfQHI
- **Gallery:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/213

Pizza Ghar: Multimodal Voice AI for Real-World Restaurants

We didn't build a hackathon mockup. We built a production-ready Voice AI system for a LIVE restaurant client in Nepal.

The Problem: Small shops in Nepal run on WhatsApp, but taking orders manually is chaotic. Generic AI chatbots fail on Nepali accents and Hinglish code-switching.

The Solution: Pizza Ghar is an agentic voice ordering system built for PizzaGhar (Birtamode), running on top of our existing SaaS platform, Zappertrip (Aahwan IT Group, est. 2017), which already powers 5 live shops and 116 active customers.

The Meta AI Integration (3 Models):

Meta Muse Spark 1.3 (Text): Acts as the brain, fuzzy-matching messy transcription to our live MySQL menu and extracting strict JSON.
Meta Muse Image 1.0 (Vision): Generates a professional, combined photo of the exact cart items asynchronously while the AI speaks.
Meta Muse Voice Transcribe (Fallback STT): Integrated as a high-availability backup for speech-to-text.
Technical Depth (Zero Hallucinations by Design):
We engineered two distinct agentic personas with risk-appropriate autonomy:

Customer Agent (Deterministic): The LLM only extracts JSON. A strict Node.js state machine controls the flow, guaranteeing zero AI loops or hallucinated orders.
Owner Agent (Autonomous Text-to-SQL): The shop owner asks natural language questions (e.g., "Which items are low on stock?"). Muse Spark writes a live MySQL query (using JSON_TABLE for nested data), executes it against production, and returns the answer. We enforce strict SELECT-only guardrails.
The Closed Loop:
The system handles the full lifecycle: Voice Order -> AI Image Generation -> Owner Dashboard -> Payment Page -> Inventory Auto-Deduction.

Live Links:
Platform: https://zappertrip.com
Hackathon Demo: https://whatsapp.zappertrip.com/hackathon/
GitHub: https://github.com/sitrsh12/meta-ai-hackathon-Aahwan_IT_Group

## More from Meta Global AI Developer Hackathon

- [Zheng Zhang](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/210)
- [Coevo Caddie](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/211)
- [Felix Le](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/212)
- [Crowsnest](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/214)
- [AOT](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/215)
- [laf.](https://cerebralvalley.ai/e/meta-ai-developer-hackathon/hackathon/gallery/216)

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