
ML Data Labeling: Cleaning ML Labels for Biodiversity Projects
Automatic image capturing of animals is becoming the gold standard in biodiversity conservation. Learn how our ML models speed up the process.
We create, maintain, and develop Shiny applications for enterprise customers all over the world. Appsilon provides scalability, security, and modern UI/UX with custom R packages that native Shiny apps do not provide. Our team is among the world’s foremost experts in R Shiny and has made a variety of Shiny innovations over the years. Appsilon is a proud RStudio Full Service Certified Partner.
As an RStudio Full Service Certified Partner, we can deploy your data products with RStudio Server Pro, RStudio Connect, or RStudio Package Manager. Overall, we have the expertise and ability to assist all project stages with advanced decision support systems and ongoing support for servers and infrastructure.
Appsilon's development process is unique in our combination of unmatched rapid development and the high code quality of the solutions we deliver. As a result, we deliver world-class Shiny applications faster than other vendors. Ultimately, lowering the overall cost of development and improving time to deployment. We use continuous collaboration with clients, end-to-end testing, and automated processes to streamline the development process. Our team can step in at every phase of a Shiny project, starting from business analysis and data science consulting to code refactoring.
We've also created our own packages that make R Shiny apps more beautiful, dynamic, and secure. Our packages have been downloaded 50,000+ times and have 1600+ stars on GitHub. We develop and scale Shiny apps for enterprise customers that are capable of thousands of simultaneous users and can operate on a distributed infrastructure.
Rhino
data.validator
shiny.fluent
shiny.react
shiny.i18n
shiny.info
shiny.router
shiny.semantic
shiny.worker
Automatic image capturing of animals is becoming the gold standard in biodiversity conservation. Learn how our ML models speed up the process.
Are your R Shiny apps slow? Caching might help. Learn the top 3 ways to cache elements of R Shiny dashboards.
Try adding Google Analytics to your R Shiny app and gain valuable insights into user engagement.