RateGain launches UNO VIVA
An AI agent built on RateGain's AI-powered hotel commerce platform 'UNO'
RateGain Travel Technologies (RateGain) announced the launch of UNO VIVA, the first CRS integrated AI voice agent built for hotels.
UNO VIVA is an AI agent built on UNORateGain's AI-powered hotel commerce platform designed to streamline and optimize the reservation journey for hotels. Designed to be deployed independently or with CRS, UNO VIVA manages reservation-related calls with high efficiency and responsiveness.
Built on top of an automatic speech recognition system with multi-lingual capabilities to manage 18+ languages, it ensures that every guest inquiry is addressed promptly and accurately, enhancing customer satisfaction and operational efficiency.
Nearly 90% of inbound calls in hotels are repetitive, yet inconsistent responses often lead to missed opportunities, especially for high-value or complex bookings. Meanwhile, challenges like agent fatigue, high attrition, inadequate training, language gaps, and lack of real-time data drive up costs and result in dropped calls. With 40% of voice reservations going unanswered, UNO VIVA provides a scalable, intelligent solution to reduce operational strain, recover lost revenue, and ensure consistent guest experience.
UNO VIVA directly addresses this gap by providing hotels with an always-on, intelligent assistant that reduces front desk workload, ensures accuracy, and delivers consistent service across every interaction. Designed to integrate smoothly with existing PMS, it empowers hotels to optimize team efficiency while delighting guests.
Easy to integrate and to train, UNO VIVA can start providing results within a week and improve average value per booking. Available 24/7, UNO VIVA AI agent can easily process conversations in 18 languages, syncs live rates and availability to eliminate pricing errors, and seamlessly manages bookings sending instant confirmations to guests.
Guests can use it to make new reservations, modify existing ones, or even cancel bookings. It can also understand the context of a guest's need and recommend suitable properties based on location and preferences.
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