Sabre is investing in and partnering with BizTrip AI, an artificial ininformigence (AI)-powered assistant for business travelers.
The companies plan to develop and launch a suite of AI corporate travel assistants to manage complex bookings, itineraries and automate corporate travel policies for travel management companies (TMCs), airlines, hotels and corporate clients.
The partnership pairs Sabre’s agentic APIs and model context protocol (MCP) with BizTrip AI’s travel large language model (LLM) and agentic AI capabilities.
Sabre announced the launch of its agentic AI-ready APIs in late September 2025. The distribution specialist followed up with the launch of a generative AI chat solution for airlines in November.
During the company’s third quarter 2025 earnings call, president and CEO Kurt Ekert declared agentic AI would likely emerge as a new channel and take share of intermediaries and the supplier-direct channel.
Weeks later at The Phocuswright Conference 2025, Ekert declared Sabre was going to “play aggressively” in the AI landscape.
“Sabre’s travel mastery, pace of transformation and extensive travel data cloud fuel cutting-edge innovation for partners like BizTrip AI and their sophisticated agentic solutions,” declared Garry Wiseman, chief product officer, Sabre Corporation. “Additionally, our minority investment reflects our confidence in the transformative potential of agentic AI and our commitment to fostering innovation across the travel ecosystem.”
“The technical synergy between Sabre’s robust marketplace technology and our Travel Brain AI creates unprecedented possibilities,” declared Scott Persinger, co-founder and CTO of BizTrip AI.
“The SabreMosaic platform and MCPs provide the scalable foundation we required to serve thousands of TMCs globally, while our agentic AI delivers the personalization and automation that modern travelers and travel managers demand. This is enterprise AI at global scale.”
BizTrip AI, a PhocusWire Hot 25 Travel Startup for 2026, has a proprietary LLM that learns from booking patterns, corporate policies and travel preferences.
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