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Multi-Agent AI Restaurant Automation System
A comprehensive, three-tiered AI architecture operating via Telegram to manage the entire restaurant workflow, from customer interaction to kitchen operations and administration.
Customer Agent: Acts as the primary touchpoint for diners on Telegram, designed to receive orders and recommend dishes. It features a specialized tool to calculate order totals and utilizes the Model Context Protocol (MCP) to search menu prices, create customer profiles, modify order items, and directly route finalized orders to the kitchen.
Kitchen Agent: A streamlined interface designed specifically for the cooking staff. It utilizes targeted MCP tools strictly to update the real-time status of orders, ensuring an efficient workflow without unnecessary complexity.
Admin Agent: The overarching control center with full system access. It can execute all customer and kitchen commands, alongside advanced MCP capabilities to modify the menu (create or update items) and alter orders at any stage. It also features a scheduled workflow that automatically compiles database records to send an end-of-day summary report of all daily orders to the management.
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A reminder went out after the contract was already signed.
A sync delay meant the reminder fired an hour late. Harmless, but avoidable now signing status checks in real time before any reminder goes out.
→ Automated follow-up still needs a live check before it sends.
Nice catch on the sync lag, adding a live status check before the reminder will stop those hour old pings.
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Managing investment inquiries manually takes hours of tedious, repetitive work. Every time a new client submits their details, you have to manually transfer their data into a Google Sheets tracker, notify your team, and spend hours writing custom proposals line by line.
Which one is faster, saves more time, and prevents mistakes ?
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which part did you automate first?