Improving reproductive performance in dairy cattle is paramount to maximize dairy productivity and sustainability. Artificial insemination (AI) is the most common breeding practice for dairy cattle in the US and worldwide. It is common to observe large within- and among-herd variation in conception rate and performance of AI technicians. The objective was to assess a user-friendly application (APP) for mobile devices developed to allow the evaluation of the AI procedure under field conditions. The APP was designed to collect information during the AI procedure to allow the identification of breeding practices (e.g., semen handling, breeding procedures) that may affect reproductive outcomes. In addition, the APP generates a database for benchmarking metrics associated with performance of AI technicians. Novel components of the APP include: (1) login screen for individual users, (2) capture of farm information (e.g., type of facility, herd size), (3) sire identification, (4) semen used (sexed or conventional), (5) breeding strategies (e.g., estrous detection, synchronization programs), (6) animals inseminated (e.g., cows, replacement heifers), and (7) recording of the following metrics: number of semen straws simultaneously thawed, thawing time, AI catheter loading time, time from loading of AI catheter to the cow, time to AI, and time elapsed for each round of insemination. In addition, information is summarized to generate an electronic report, and all captured data are uploaded into a cloud database. The APP features a user-friendly interface for entering and managing data, and accurately (100%) captured, summarized and integrated multiple events associated with the AI procedure under field conditions.