Riviera — AI Voice Agents for Hospitality

What

Riviera is an AI voice and messaging platform designed for hospitality teams, especially hotels and similar guest-service properties. It handles inbound guest interactions across calls, SMS, email, and chat, with a focus on answering routine questions, taking service requests, supporting reservations and dining orders, and transferring complex issues to staff with context attached.

The product appears positioned as an operations layer for front desk, concierge, reservations, and guest services teams that need 24/7 responsiveness without pulling staff away from in-person service. Its workflow centers on loading hotel knowledge, configuring agent flows visually, using guest context during conversations, and monitoring live interactions through a dashboard with analytics and AI-generated insights.

Features

• 24/7 AI guest handling: Riviera answers calls and messages around the clock so hotels can respond even during overnight hours, peak check-in periods, or simultaneous inbound requests.
• Multilingual voice conversations: The system detects a guest’s language from the first words of a call, switches automatically, and can continue if the guest changes languages mid-conversation.
• Omnichannel guest communication: Calls, texts, email, and chat are managed in one environment, which can help teams keep guest communication consistent across channels.
• Guest context before answer: Caller ID can load stay details, preferences, and prior interactions before the conversation starts, enabling more personalized and efficient responses.
• Visual workflow builder and human handoff: Teams can configure agent roles, voices, and routing logic with drag-and-drop tools, then transfer to staff with summaries, transcripts, and guest context included.
• Knowledge base and operational insights: Hotels can upload policies, menus, and FAQs for the AI to use, while dashboards and AI Insights surface trends, common complaints, and repeat question patterns.

Helpful Tips

• Validate source content carefully: For hospitality AI systems, accuracy matters more than breadth, so confirm that policies, amenity hours, reservation rules, and exception cases are current before deployment.
• Design escalation paths early: Map which guest issues should stay automated and which should go directly to a human, especially complaints, VIP cases, billing concerns, and urgent service failures.
• Pilot by department or use case: A phased rollout covering common tasks like late check-out, spa booking, or basic FAQ handling is usually easier to govern than a full-property launch on day one.
• Review analytics for operational fixes: Insight tools are most useful when teams act on recurring guest questions and complaint patterns rather than treating analytics as reporting only.
• Check integration depth during evaluation: The site references reservation context and, on higher-tier plans, custom PMS and POS integrations, but buyers should verify exactly which systems and workflows are supported in practice.