SaaS · Web App · AI · Restaurant Tech · 2025
SyntheCRMS — AI Restaurant Management SaaS
Complete AI-powered restaurant operating system: POS, kitchen display, online ordering, inventory, multi-branch, 24/7 AI call center, WhatsApp auto-order bot, AI menu writer and Mushak 6.3 billing — end-to-end SaaS demo.
- Screens
- 40+
- AI surfaces
- 3
- Build time
- 6 wks
- Tenants
- Multi + white-label
- Client
- SyntheStudio (portfolio demo)
- Year
- 2025
- Timeline
- 6 weeks
- Categories
- SaaSWeb AppAIRestaurant Tech
- Role
- Founding Full-Stack Developer
- Services
- Product architectureFull-stack developmentAI integrationUX designSEO & schema
- Stack
- ReactTypeScriptViteTailwindCSSshadcn/uiReact RouterTanStack QueryZodRechartsSupabaseOpenAIWhatsApp API
The challenge
Restaurants juggle POS, kitchen tickets, online orders, delivery aggregators, inventory, tax billing and phone reservations across half a dozen tools. The demo had to prove one AI-native SaaS could run the entire operation — front-of-house, back-of-house and off-premise — while staying compliant with local (Mushak 6.3) tax rules.
My approach
Modeled the restaurant as three connected surfaces — front-of-house (POS, tables, reservations), back-of-house (KDS, inventory, recipes, wastage, suppliers, purchase orders) and off-premise (public QR menu, online ordering, aggregators, WhatsApp bot, AI call center). Layered AI across the stack: menu writer for merchandising, WhatsApp bot for auto-orders, and a 24/7 call center agent for reservations.
Key features
- POS with tables, orders and split billing
- Kitchen Display System (KDS) with live tickets
- Online ordering with QR public menu
- Inventory, recipes, wastage and purchase orders
- 24/7 AI call center for reservations
- WhatsApp auto-order bot
- AI menu writer and menu engineering
- Mushak 6.3 tax-compliant invoicing
- Multi-branch + white-label + super-admin
- Delivery aggregator integrations
Technical decisions
Three-surface architecture
Front-of-house, back-of-house and off-premise modeled as distinct surfaces sharing one data layer — matches how restaurant teams actually work and keeps each screen focused.
AI as first-class operator
AI is not a chatbot bolted on: it takes reservations by phone, auto-writes menu copy, and closes WhatsApp orders end-to-end — real operational leverage, not novelty.
Local tax compliance built-in
Mushak 6.3 invoicing shipped as a first-class module so the demo is credible for the Bangladesh market, not just a generic Western POS.
Multi-branch + white-label from day one
Super-admin, tenant isolation and white-label branding built into the schema instead of retrofitted — the demo can be pitched to chains, not just single outlets.
Outcome
A fully navigable multi-branch restaurant SaaS demo used as an Upwork work sample: 40+ screens covering POS → KDS → inventory → Mushak billing, plus AI call center, WhatsApp order bot, AI menu writer, aggregator integrations, white-label and super-admin — all behind a single sign-in.