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Deem and OLSET Join Forces to Create Smarter Travel Technology

Leading-Edge AI, Machine Learning and 200 Million Sentiments from 60 Million Hotel Reviews Will Bring New Level of Personalization to Business Travel Software

SAN FRANCISCO, CA--(Marketwired - October 19, 2016) - Deem, a leading mobile and cloud technology solution provider for the business travel industry, announced today that it has entered into an agreement to acquire the assets and personnel of OLSET, a leading big data and machine learning technology company. In combination with Deem's industry-leading travel software, OLSET's technology will enable Deem to provide a new level of personalization and optimized booking experiences for business travelers, while offering travel management companies and content providers additional revenue at no incremental cost.

"OLSET has been a trailblazer in using AI and machine intelligence to drive personalization in travel software," said John F. Rizzo, President and COO of Deem. "This acquisition is a great opportunity to harness the synergies between our products and create the next generation of travel technology. It adds more fuel to Deem's innovation efforts made possible by our recent funding, renewed focus and new leadership."

The announced acquisition was greeted with enthusiasm by leading business travel services and Deem customers. "American Express Global Business Travel (GBT) is constantly exploring new technologies to improve the services and products we provide to our customers and partners," said Evan Konwiser, Vice President of Digital Traveler at American Express Global Business Travel. "The machine learning and AI technology that Deem will provide based on the OLSET platform is very promising, and we're pleased OLSET is now a part of the Deem ecosystem."

"This is an exciting development for the industry," said Ivan Imana, CIO of Adelman Travel. "The new technology will have a big impact on hotel attach rates for us, resulting in higher client satisfaction."

OLSET's technology includes a knowledge-based recommendation engine, machine learning, sentiment analysis and natural language processing. These are used to analyze past user behavior, traveler profiles and large quantities of data -- including 200,000,000 sentiments extracted from more than 60,000,000 reviews of more than 500,000 hotels -- to better match users with hotels and other services. This high level of personalization will enable Deem to significantly increase hotel "attach rates": the rate at which employees use company-compliant software to make hotel reservations after booking flights.

As a result, employees benefit from a faster, more convenient booking experience. Corporate travel managers and travel buyers can better control spending by ensuring that that employees do more of their booking using approved systems and preferred providers. And content suppliers get best-of-breed tools for consumer-grade offer optimization to present their content to the most likely buyers and thus generate more revenue.

OLSET was funded by capital from a number of leading venture capital firms including Amadeus Ventures and Montage Ventures. The transaction is slated to close in the next 45 days, and plans are already underway to integrate the OLSET technology into Deem's platforms.

About Deem

Our mission is simple. We make business travel less complicated for travelers, less costly for employers and more profitable for service and content providers. Using our industry-leading software solutions, employees book travel and car service and report those expenses faster and more easily than ever before. Corporations control costs more effectively. Travel management companies deliver more engaging customer experiences. Car service operators benefit from new efficiencies and widen their customer reach. We've helped thousands of forward-thinking companies modernize their systems, improve travel management and save big money. Deem is backed by leading venture capital funds as well as corporate and private equity investors. The company is headquartered in San Francisco, CA.

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