Reply announced that it has developed an end-to-end solution architecture for autonomous mobile robots (AMR) on Microsoft Azure that enables new business applications across industries, reduces upfront costs and allows for the rapid implementation of customer-specific robotics use cases. The solution combines Microsoft Azure services, the agility of Boston Dynamics' SPOT and Reply’s knowledge of intelligent cloud computing services, edge computing and artificial intelligence. To demonstrate the capabilities of a scalable and versatile robotics platform, Reply implemented an automated vehicle-damage-detection solution for rental or leasing companies that leverages this architecture. In fact, rental or leasing companies must inspect vehicles for any damage after they are returned in order to ensure the safety and quality of their fleet for their customers. This is usually done in the time- and cost-consuming manual process of walking around the car, visually inspecting it, assessing the severity of the damage and conducting a damage report. Reply integrates Azure Cognitive Services, Machine Learning and DevOps as well as Power Apps and Power BI. Thanks to Azure's intelligent service foundation, agile workflows and machine learning, this process can be fully automated. Using computer vision, SPOT moves freely through the parking area and scans the license plates to find the right vehicle. Once detected, it walks around the vehicle to record its condition by continuously collecting visual data with its camera and sensors. This information is processed “on the edge” or transmitted to the cloud, where advanced image recognition and machine leaning algorithms perform the damage detection. All detected damages are saved in the return protocol, and they can be presented to the customer and the fleet manager for approval. With their agility, autonomous mobile robots (AMR) are able to move independently from a central infrastructure on terrain that is not traditionally designed for robots. They can be used in hazardous environments and environments, that are harmful to people.