IndustryNews Launches Online Booking Tool for the Corporate Sector has launched a new online booking tool aimed at the corporate sector. The region’s sole homegrown travel provider aims to usher its 900+ corporate clients into a new age of business travel with this augmentation to their unrivalled portfolio of services.

In a bid to modernize business, the new online tool will feature:

Advanced travel policies: These help companies stay on budget with 20+ control checks including airlines, cities, classes, refundability, and rating.

Automated profiles: This allows for the efficient import of all employee passport details and preferences or connects with single sign-on.

Easy to track spends: Tags are used to monitor spends and segregate them by department, designation, cost centre, travel intent and more.

Paperless approvals: Detailed approval requests are sent to line managers and CEOs with one-click processing.

According to, these key features coupled with the ability to obtain real-time reports and insights, are likely to result in up to 20 percent travel budget savings for clients.
At the center of the tool is its machine learning function that is constantly evolving to give travelers different options based on their previous filters and preferences.

“We have invested heavily in end-to-end automation on the corporate travel front. From the booking process to the reporting, we’ve leveraged algorithmic machine learning to make business travel a seamless experience,” says Sachin Gadoya, CEO, “As we continue to grow technologically, we will also branch out geographically. We’re steadily expanding further into the Middle East and India markets and are in talks to progress into key economies in South East Asia as well.”

The company recently announced that they’re on track to achieve a 30 percent year-on-year growth in their corporate business by the end of 2019 and cross 100,000 transactions, Dias attributed this success to its digital transformation journey, which began in 2018, and uses innovative technology such as machine learning and natural language processing to optimize travel planning.


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