Avenlo House / Toronto

Today

Live operations Day shift
Fictional property. Prototype operational data.

This console demonstrates how Kodawa Labs translates hospitality research into decision support. No real guest or property data is shown.

Rooms 31 / 38

Occupied tonight

Arrivals 12

3 before 15:00

Luma 46

Covers tonight

Gather 1

Event / 40 guests

Members 17

Currently in-house

Exception management

Needs attention

4
12:15 Arrival
Early arrival Room 318

Maya Thompson

Guest arrived 2h45 before standard check-in and asked for somewhere to work.

Room readiness 72% Member No Luggage 2 bags
Recommended next step

Offer lounge access, notify housekeeping of early presence, and message Maya when the room is ready.

18:30 Dining
Safety acknowledgement Luma / Table 14

Jordan Lee +2

Shellfish allergy was captured during the guest conversation. Kitchen acknowledgement is still pending.

Severity Serious Kitchen Pending Reservation 18:30
Required action

Confirm the restaurant team has reviewed the allergy information before service begins.

17:45 Gather
Event arrival Garden Room

North & Vale Workshop

Forty-person workshop begins at 18:30. Client host is expected in 30 minutes.

Guests 40 Room Ready AV check Complete
Next checkpoint

Confirm host arrival and hand the event lead the final guest-count context.

11:42 Service
AI handoff Guest services

Transfer request

Guest asked whether Avenlo can arrange a helicopter transfer. The AI did not have verified information and escalated the conversation.

AI answer Withheld Context Preserved Status Open
Why this matters

The operator receives the original request and context without requiring the guest to repeat the conversation.

01 AI when it knows.
02 Human when it matters.
03 Context preserved either way.
Action completed