R and Shiny Consultancy

R SHINY CONSULTANCY

WORKSHOPs AND TRAINING

Data strategy
hypebright's R/Shiny Expert.
Hi! My name is Veerle Eeftink – van Leemput and I’m the director of Hypebright BV. I’m a passionate R-enthusiast who specializes in R and Shiny consultancy.
After graduating as Bachelor of Business Economics I graduated cum laude from my Master Data Science at Tilburg University. After studying, I immediately started working as Data Scientist. First at a large energy company, Eneco. After that at a large pharmaceutical company, Dr. Reddy’s. At both Eneco and Dr. Reddy’s I contributed to delivering data driven products. Projects I’m still very proud of!
Since the founding of Hypebright in 2019, I offer R consultancy. Since my graduation in 2015 I’ve been programming in R on a daily basis. And it went beyond programming: I also specialized in setting up the right infrastructure to leverage R within organizations.
I really enjoy helping people and organizations with their R adventure- that’s why I founded Hypebright. R is an awesome programming language, but it can be hard for organizations to figure out how to use R in a professional and scalable manner. And for individual R programmers within organizations it can be just as hard to find the right support and training. That’s exactly where I come in with R and Shiny consultancy!
Specialization.

R
R is perfect for statistical analyses, but also for developing advanced analysis tools and retrieving and cleaning data.

Shiny
With Shiny it's possible to develop web applications. From dashboards to enterprise-grade software, everything is possible with Shiny.

Workshops
I love sharing my knowledge about using R. Through R Shiny training and workshops I help to you and your team to get the most out of R.

Public speaking
As an active R community member I'm regularly appearing at conferences, meetups and podcasts to talk about various R and Shiny topics.

20+
Complete Shiny applications

9
R packages

50+
Mentoring sessions

8
Years of experience
consultancy & Training.
R Programming
I program in R on a daily basis. Whether it’s setting up ETL processes, managing operational processes, or analyzing data. Because of my practical experience with using R in organizations I’m well equipped to help other organizations too.
Most of the projects I’m working on aren’t open-source, but feel free to find out a little bit more about me on my GitHub profile 🐱 .
R Shiny
Shiny is so much more than a tool to create dashboards. With Shiny you can build full-blown enterprise-grade applications! I made it my personal mission to show people around the world what Shiny is capable of and how organization can efficiently make scalable and fast web applications. Shiny developers are also software developers. That means that you also have to be aware of best practices within software development. From UI/UX design to user management, data management, scaling and optimizing. You can only build a Shiny app with a good plan.
Can’t wait to hear more? I gave a talk at the Posit (RStudio) Enterprise meet-up about optimizing Shiny for enterprise-grade apps where I go into more detail 🎥 .
Data Pipelines & data analytics
Data is incredibly valuable. You just need to know how to access the right data and extract valuable insights from it. How do you gather the best data, where do you store it, and how can you efficiently and effectively extract information from this data?
I assist organizations in managing their data storage, setting up data pipelines, deploying models into production, and translating data analyses into understandable language and visuals.
And all of this is only possible with the right infrastructure, such as Azure databases, VMs, APIs, App Services, Docker, CI/CD, Posit Workbench, Posit Connect, and Posit Package Manager. Together, we will create a solid and robust foundation.
Training & Workshops
Staring with R or Shiny can be daunting for teams and individuals. How do you make the switch from Excel or PowerBI to R? Or how do make your current R data pipelines more efficient and Shiny apps production-grade? Perhaps your team is already working with R and Shiny for quite some time, but is currently lacking the structure to collaborate efficiently and effectively.
Every organization is different, and every team is different. This means that the best solution, or the best way of working together, is different as well. Training should take these differences into account.
The trainings and workshops I provide are completely tailored to your needs. This means that I will first chat with you and your team about the specific needs. Together we will make learning goals and a planning. During the training or workshops we preferably work with your own data: this way you can immediately put into practice what you learned. Depending on your location, the trainings and workshops can be offline or online. In 2024 you are also welcome at our own training facility in South-Holland.
Feel free to reach out for an exploratory chat!
Blog.

So… What’s the deal with rlang, anyway?
So… what is rlang, anyway? And why is it so powerful? If you’re familiar with the tidyverse and/or looked at package dependencies, you’ve probably seen rlang pop up and wondered what on earth it’s doing there. In this article, we’ll take a look at what rlang actually is, how it fits into R’s world, how you can use it yourself, and what kinds of things it makes possible. We’ll keep it simple, skip deep technical explanations, and look at a few short examples to make sense of why this little package shows up everywhere. Basically just like you’re used to when it comes to my writing! What rlang actually is Usually a good place to start understanding a package is by reading the package documentation. In rlang‘s documentation we find: “rlang is a collection of frameworks and APIs for programming with R”. Hmmm… Not quite the one-liner that explains it

Using LLMs in Shiny (for R & Python): The Shiny Side of LLMs
You might have seen The Shiny Side of LLMs pop up on the Shiny blog, which is my latest three-part blog series written for anyone who wants to understand what large language models (LLMs) actually do, and how to use them in a Shiny app. It’s a complete (mini?) guide on how to work with LLMs in both Python and R. Why I wrote this series Before we jump into the summaries, here’s a bit of background on why I wrote it. When I started exploring LLMs, I found the online explanations either too high level or way too complicated. Often they were full of mysterious jargon and missing the “why”. As I wrote on LinkedIn: I don’t like things to be boring or overly complicated. And in the fast-moving world of LLMs it’s easy to get lost in all the mysterious jargon. I prefer plain English, a bit of

Customizable Select with Chrome 135 (and Shiny!)
Select inputs, aka dropdowns or pickers, show up on nearly every web page or app, but their default look is pretty… basic. Or to put it differently: it’s sometimes even downright ugly. That’s because browsers handle most of their styling, using the system’s native styles, which makes customization tricky. Your normal CSS styling becomes pretty much useless. The usual fix is turning to JavaScript libraries like selectize.js, which Shiny also uses by default. It makes select inputs look nice again! But wouldn’t it be nice if you can also style select inputs entirely with CSS? With Chrome 135 (April 2025), you finally can. A feature that has been long awaited! Styling icons, checkmarks, dropdown lists: all possible. You just need to know which properties you can style. In this article, I’ll walk you through how to switch off selectize.js in Shiny and start taking advantage of this new customizable select

Shiny Source Code Explained: Secrets of Observers
Shiny’s reactive system has a few key players, and one of them is observers. The idea is pretty straightforward: whenever there’s a change in a reactive value or input, you want to do something. Shiny observers make that happen. But there’s more than meets the eye: observers have their little secrets! Before we can uncover any secrets, it’s good to take a step back first and focus on what observers actually are. Which functions are we talking about, and what characteristics do Shiny observers have? After that, it’s time to get into Shiny’s Source Code to see how observers actually work under the hood. What hidden methods exist, and how can you use them in your next Shiny app? All that (and more) in this edition of “Shiny Source Code Explained”! Table of Contents Observers: what do they do? Observers, such as observe(), observeEvent(), and the more recent combination with bindEvent(),
Contact.
Hypebright BV
Veerle Eeftink - van Leemput,
R and Shiny consultant
Contact
Tel: +31 6 54 61 22 64
E-mail: info@hypebright.nl
Address
Schenkeldijk 59A, 3291 EN, Strijen, The Netherlands