ℹDemonstration scenario. An example of a possible implementation, not a completed client project of Neural2B.

AI Assistant for Booking and Orders in the Venue

Demonstration scenario: the venue's website and agreed messenger, menu from a controlled catalog, booking request confirmed by the administrator.

Business situation overview

Restaurants and cafes often lose guests in the evening and during peak hours. The administrator is busy with the hall or billing, and no one answers calls and messages on Telegram/Instagram — 'is there a table?', 'what's on the menu?' — the guest goes to the neighbors.

Data flow and architecture diagram

1Channel: Telegram bot and widget on the venue's website

2Menu: controlled database of dishes, prices, ingredients, and allergens

3Time check: the venue's working hours and available seating areas

4Integration: the request goes through a webhook or API (candidate — Poster, after technical verification)

The human role in the loop (Human-in-the-loop)

The AI assistant only collects the preliminary request with all details. The booking is finally confirmed by the administrator — after checking what is happening in the hall.

Synthetic test data

Example input and system response

User input request:

"Good evening! Do you have a table for 4 tomorrow around 7:30 PM? And are there gluten-free dishes?"

Generated response / system action:

"Good evening! Tomorrow at 7:30 PM there are free seats in the main hall. Regarding dishes: we have a separate gluten-free menu (for example, quinoa salad and pike perch fillet). Would you like to make a preliminary request with your name and contact number?"

Limits of the demo scenario

✕Without manual confirmation from the administrator, the booking is not guaranteed
✕Prices and dishes — strictly from the current menu
✕Conflict issues or complaints go directly to the manager

What to measure during pilot testing

✓How long on average does a guest wait for the first response (goal: < 10 seconds)
✓How accurately are contacts and times recorded (goal: > 98%)
✓What percentage of conversations required immediate human intervention

Relevant company service

AI Chatbots for Sales and Support

Service overview →

Interested in a similar architecture?

We’ll adapt the logic of this scenario to your internal software, database structure, and operating rules.

Discuss adaptation

Other scenarios

Scenario adaptation: AI Assistant for Bookings and Orders

Describe the process that’s eating up your team’s time. We’ll suggest what can be automated, what data is needed, and where to start.