Restaurant recommendation use case

An AI business-dinner restaurant finder built around avoiding mistakes

A business meal is a practical hosting decision. The restaurant must support the conversation, protect the host from avoidable surprises, and fit the guests—not merely look expensive.

Start with the facts that change the shortlist

Beijing

北京商务请客,6 个人,需要包间、停车方便。环境要稳重,但不要太浮夸。


English

Find a reliable business-dinner restaurant for six people near our client’s office. We need a quiet table or private room, straightforward parking, and vegetarian options.

If the neighborhood, budget, guest preferences, or time is missing, the agent should ask before searching when that answer can materially change the candidates.

Private room or quiet table

“Good for groups” does not prove that a private room exists. Treat room availability, minimum spend, capacity, and reservation rules as details that require current evidence or direct confirmation.

Arrival and parking

Check whether guests are arriving by car, taxi, or public transport. A useful recommendation distinguishes verified parking information from a general map assumption.

Formality and noise

The right level is often polished and dependable rather than theatrical. Conversation comfort, table spacing, service pace, and music matter more than social-media popularity.

Guest and menu constraints

Dietary requirements, disliked cuisines, allergies, sharing style, and alcohol expectations are operational constraints. They should be resolved before novelty is optimized.

Budget and timing

Clarify whether the budget is per person, includes drinks, and is a hard ceiling. Also check the meeting end time, restaurant closing time, kitchen hours, and expected meal duration when those facts are available.

What an evidence-backed 2+1 looks like

  • Safest fit: the most reliable match for access, privacy, guest needs, and formality.
  • Alternative fit: a credible option with a useful tradeoff, such as easier transport or a more flexible menu.
  • Exploration choice: a more distinctive restaurant, explicitly labeled when the evidence or operational fit is less certain.

Each recommendation should state why it fits, what could go wrong, and what the host must confirm. A rating alone is not a business-dinner explanation.

Facts Nomtiq must not invent

Private-room availability, parking validation, current price, opening hours, minimum spend, dietary accommodation, and booking availability can change. Nomtiq should cite live support where available, state uncertainty elsewhere, and suggest confirmation before departure. The core recommends restaurants; it does not contact a venue or make a reservation.