Sabre has launched an artificial intelligence (AI)-powered retailing platform designed to enable airlines to adopt an “offer and order” approach.
The new SabreMosaic platform allows airlines to offer a more personalized and dynamic retailing experience and create new revenue opportunities, the company said in a Wednesday (May 22) press release.
“SabreMosaic is the culmination of our dedication to innovation in airline IT and active collaboration with our airline partners to enable the future of modern retailing,” Kurt Ekert, president and CEO of Sabre, said in the release.
The platform is powered by Google’s AI and Google Cloud technology, according to the release.
With these technologies, SabreMosaic enables airlines to select “offer and order” solutions that best meet their needs, create a unique technical blueprint for their operations, and create, sell and deliver personalized content to travelers, the release said.
SabreMosaic includes 10 new product suites encompassing everything from offers and orders to settlement and delivery, per the release. It also includes Sabre’s existing AI-powered Retail Intelligence solutions.
“Airlines are becoming sophisticated retailers and need the same data-driven insights and AI tools to optimize their businesses and better serve their customers as other consumer services,” Thomas Kurian, CEO of Google Cloud, said in the release. “Through our work with Sabre, we are helping airlines harness their data to make faster, more informed decisions that improve operations, personalize marketing and ultimately increase customer satisfaction.”
Another AI-powered platform that is helping airlines navigate the complex dynamic pricing world is offered by Fetcherr.
Fetcherr’s AI technology uses reinforcement learning models to simulate pricing scenarios and determine the most profitable strategies under market conditions, with its large language model (LLM) enabling “high-frequency, informed decision-making,” Fetcherr CEO and co-founder Roy Cohen told PYMNTS in an interview posted Friday (May 17).
“Just as reinforcement learning is a domain of machine learning in which an agent optimizes its behavior through interactions with a dynamic environment, guided by the feedback of rewards or penalties, Fetcherr uses models to continuously improve and optimize airline revenue management strategies,” Cohen said.
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