24/7 multilingual concierge across 6 FL beach resorts62% of guest requests resolved by agents — no overnight desk staffing.
The operational reality.
FL beach-resort group, 6 properties, $42M revenue. Summer demand spikes 4x baseline; multilingual guest mix (English, Spanish, Portuguese, French) overwhelms front desk; review volume across OTAs unmanageable; revenue manager only touches dynamic pricing on 3 of 6 properties.
What we ship.
Concierge agent on web, SMS, WhatsApp, and in-room handles guest requests in native languages — escalates to human staff on edge cases. Pricing agent ingests PMS + comp set + demand signals to surface yield opportunities. Review-response agent drafts brand-voice replies across OTAs/TripAdvisor; humans approve in seconds.
The agent topology + Microsoft AI stack.
Agents (Microsoft Agent Framework 1.0)
- Multilingual concierge
- Pricing & yield
- Review-response
- Group sales follow-up
Models
- GPT-5.4 Mini (concierge)
- MAI-Voice-1 (calls)
- Claude Opus 4.7 (brand voice)
Tools (MCP)
- Opera/Mews PMS
- Toast POS
- OTA APIs
- Demand-signal feeds
Governance
- Agent 365 per property
- Brand-voice eval harness
- Purview for guest data
What we engineer toward.
Guest requests fully resolved by agents
62%
RevPAR lift on slow-day inventory
+8.4%
Multilingual coverage 24/7
100%
Group-sales response time
Days → mins
What we use.
Reference scenario. Architecture is the one we ship today; metrics are directional benchmarks drawn from industry data and Microsoft customer reference outcomes. Named, attributed customer stories will be published as engagements mature.
Pattern look like yours?
Tell us the pain and we map it to the right reference architecture. End-to-end proposal back in 5 business days.