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Inside AlarisPro
At Alaris, our foundation began with decades of military aviation experience long before the emerging UAS industry took off. We took interest in improving information to support safe UAS flight and grew our fleet. We leveraged our combined experience to capture the best ideas for inputting, storing, and reporting data.  Far from the days of scribbling on pink sheets and filling out log books in maintenance control, we wanted to use the latest software, smart phones, tablets, computers, and ubiquitous internet access. 
But we didn’t stop at creating logbooks.  There are plenty of companies offering online flight and maintenance logs.  AlarisPro is much more!  Our software securely compiles individual data across fleets of UAS to create meaningful information to support Operators and Manufacturers of UAS and their supporting components. This is a game changer.  AlarisPro allows companies to see important metrics like “Mean time between failure” and “Average time in service” for fleets of UAS – not just their own.  These metrics are critical to manufactures wanting to stand out in an industry with thousands of competitors. 
AlarisPro was born from this necessity.  Our business partners saw what we were doing and realized how much it could help distinguish them from their competitors.  Starting with a few trusted friends and companies, we kept asking what else we could do to make everyone’s job easier and our product better.  At the same time, we continued to use our software in the field and back at the office.  As a company that uses AlarisPro on a daily basis, we are one of our most demanding customers. Try AlarisPro for yourself or ask for a personal demo. 

We’re confident that you’ll agree – AlarisPro is what our growing UAS industry needs. 









AlarisPro is the leader in UAS Fleet Management and Predictive Maintenance. We arm UAS operators, maintainers, and manufacturers with the data needed to obtain and maintain the peak performance of their unmanned systems and subsystems.   


Pioneering UAS Fleet Management and Predictive Maintenance.

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