Sabre deploys agentic AI as Linex expands globally

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Sabre Corporation, a leader in AI-native technology, has announced a pivotal deployment of its agentic AI technology with Linex Travel, formerly Ultra Group. This collaboration is part of Linex Loyalty's global expansion, following its acquisition by Linex Capital, a private equity firm specialising in loyalty and rewards. The integration of Sabre's Model Context Protocol (MCP) server aims to revolutionise travel servicing by embedding advanced AI into Linex's loyalty redemption marketplace.

The deployment of Sabre's agentic AI technology is set to transform travel industry operations by automating complex processes traditionally requiring manual intervention. Sabre's MCP server acts as an intelligent translation layer, allowing AI agents to manage intricate post-booking tasks such as ticket reissues and dynamic exchanges. Garry Wiseman, President of Product and Engineering at Sabre, stated, "True innovation is about putting production-grade AI into the heart of mission-critical travel workflows."

Linex Travel, a prominent player in the Latin American travel loyalty sector, manages rewards infrastructure for major banking clients across 12 countries. The collaboration with Sabre is expected to enhance Linex's ability to integrate loyalty programmes into AI-driven travel environments, offering seamless user experiences. Andres Peláez, CEO of Linex Travel, emphasised the importance of this partnership, saying, "By becoming one of the first in the industry to commercially deploy Sabre's MCP architecture, we're able to flatten operational friction today whilst building a scalable and secure marketplace."

As Sabre continues to lead in AI innovation, this partnership underscores its commitment to transforming travel retailing and servicing through intelligent, connected experiences


This story was selected and published by a human editor, with content adapted from original press material using AI tools and checked by the editor before publication. Spot an error? Report it here.

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Sabre deploys agentic AI as Linex expands globally

Sabre Corporation, a leader in AI-native technology, has announced a pivotal deployment of its agentic AI technology with Linex Travel, formerly Ultra Group. This collaboration is part of Linex Loyalty's global expansion, following its acquisition by Linex Capital, a private equity firm specialising in loyalty and rewards. The integration of Sabre's Model Context Protocol (MCP) server aims to revolutionise travel servicing by embedding advanced AI into Linex's loyalty redemption marketplace.

The deployment of Sabre's agentic AI technology is set to transform travel industry operations by automating complex processes traditionally requiring manual intervention. Sabre's MCP server acts as an intelligent translation layer, allowing AI agents to manage intricate post-booking tasks such as ticket reissues and dynamic exchanges. Garry Wiseman, President of Product and Engineering at Sabre, stated, "True innovation is about putting production-grade AI into the heart of mission-critical travel workflows."

Linex Travel, a prominent player in the Latin American travel loyalty sector, manages rewards infrastructure for major banking clients across 12 countries. The collaboration with Sabre is expected to enhance Linex's ability to integrate loyalty programmes into AI-driven travel environments, offering seamless user experiences. Andres Peláez, CEO of Linex Travel, emphasised the importance of this partnership, saying, "By becoming one of the first in the industry to commercially deploy Sabre's MCP architecture, we're able to flatten operational friction today whilst building a scalable and secure marketplace."

As Sabre continues to lead in AI innovation, this partnership underscores its commitment to transforming travel retailing and servicing through intelligent, connected experiences


This story was selected and published by a human editor, with content adapted from original press material using AI tools and checked by the editor before publication. Spot an error? Report it here.

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