Our client, a US government contractor, faced challenges with their canine behavior evaluation process, burdened by time-consuming manual paperwork and reporting procedures. To streamline and optimize this crucial task, they sought a bespoke Microsoft Surface application.
The client, a prominent US government contractor responsible for canine behavior evaluation, approached App Maisters with a critical objective in mind. They sought to develop a comprehensive application that would revolutionize their canine behavior tracking process. The government required a streamlined solution to record and monitor canine interactions with specific odors, eliminating the burden of excessive paperwork and manual management. The primary goal was to empower evaluation officers with a user-friendly digital platform that efficiently captures behavioral data, enables quick data access, and provides comprehensive data summaries. By achieving this, the client aimed to equip their officers with the necessary tools to make well-informed decisions while maintaining an auditable database of canine test results and video recordings for reporting and compliance purposes.
In response to the client’s need for efficient canine behavior evaluation, App Maisters proposed an innovative solution utilizing Microsoft Surface technology. The touch-based application empowered evaluation officers to seamlessly record canine responses and non-responses in a user-friendly Matrix, categorized as examined, good, and bad responses. The app facilitated easy transitions between evaluations, with comprehensive data reports available for each canine and handler, encompassing odors, targets, and non-targets. This data was downloadable and shareable via email, stored in a centralized repository for historical reporting and analysis. The implementation encompassed requirements gathering, user-friendly interface design, thorough testing, and deployment, resulting in an efficient and secure solution for streamlining canine behavior evaluations within a government context.