Applied aquaculture research sometimes fails to have impact, especially when findings are communicated via scientific publications that are inaccessible to those outside the academic field. Researchers can boost real-world impact by collaborating with industry partners, holding workshops, and publishing plain-language news articles. Another approach is to develop interactive apps, ranging from simple educational tools to complete planning tools that perform complex analyses on user inputs. This type of app development has become far more achievable with the shiny package for R. We developed a shiny app that provides site-specific parasite-prevention advice for over 1000 Norwegian salmon farms. Sea lice, especially salmon lice (Lepeophtheirus salmonis) are the perhaps the greatest challenge facing Atlantic salmon aquaculture globally. Effective treatments have side effects, so farmers are increasingly looking to prevent infestations by installing barriers than span the highest-risk depth bands, preventing the planktonic larvae from entering sea-cages. However, the intensity and depth of infestation pressure varies through time and between sites, making it difficult for farmers to implement these strategies optimally. We investigated how salinity, temperature, density, currents, and waves influence the efficacy of lice barriers, and by combining this knowledge with local predictions from a national-scale hydrodynamic model, generated bespoke initial recommendations for every active salmon farm in Norway. This information, including the hydrodynamic data underlying the recommendations, is made available to farmers via a free web app and an open-access data archive.