Explore our Services

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Methodology consulting

  • Data analysis and statistics
  • Machine learning
  • Artificial intelligence
  • Experiment design
  • Method development
  • Data and text mining
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Scientific programming

  • R, Python, Julia package development
  • Code review and optimization
  • Porting code to low-level languages
  • Parallel and distributed computing
  • In-database data science
  • GPU / FPGA programming
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Application Development and Integration

  • Desktop and web applications
  • Automation of analyses or predictive modeling
  • Data science APIs
  • Scientific data stores
  • Big data architecture
  • Data science tooling
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Data Science Platforms

  • Data analysis orchestration
  • Machine learning platform design
  • Data science infrastructure setup and hosting
  • Data science APIs as a service
  • Managed services for scientific data stores

Discover our Products

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Architect

  • IDE for data science, state of the art
  • Comfort and productivity for the R, Python and Julia developer
  • Support of low-level languages (C, C++, FORTRAN)
  • Server version for teams and HPC environments
  • Fully open source, including all enterprise features
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ShinyProxy

  • Shiny app deployment for companies and large organizations
  • Highly scalable design using Docker infrastructure
  • Authentication and authorization, single-sign on deployments
  • Usage statistics and administrator views
  • Fully open source, including all enterprise features
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R Service Bus

  • Middleware for automation of R-based jobs
  • Rich set of supported protocols (REST, SOAP, e-mail protocols, etc.)
  • Integrated management of multiple R pools for distributed computing
  • Synchronous and asynchronous APIs, admin API
  • Supports plain R scripts and packages out of the box
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RDepot

  • Corporate management of R package repositories
  • RESTful APIs for package submission and repository generation
  • Authentication and authorization for actions on multiple repositories
  • Support of continuous integration infrastructure
  • Highly available repository set-up and full audit trails

Case studies

Learn more

From our blog

Hash-tag baby

on July 3, 2025

Introduction Naming a baby can be a difficult task. It can take - soon to be - parents quite some time to align on a name they both like. Afterwards it can also be challenging to keep the name a secret until birth. If you are lucky, there might be some close friends or colleagues who are simultaneously expecting a child. It can be an unique occasion where you can share experiences.

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checkglobals: an(other) R-package for static code analysis

on March 25, 2025

Introduction An important aspect of writing an R-script or an R-package is ensuring reproducibility and maintainability of the developed code, not only for others, but also for our future selves. The modern R ecosystem provides various tools and packages to help organize and validate written R code. Some widely used packages include roxygen2 (for function documentation), renv (for dependency management and environment isolation), and testthat, tinytest and Runit for unit testing[1].

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Getting started with Crane

on March 4, 2025

As the Common Crane (Grus grus) is migrating back to their breeding area, it’s time to set up your own Crane server. Crane is a new open source product to host data science artifacts: data analysis reports, documentation sites, packages and libraries, you can read the introduction blog post here. This post provides a simple setup to get started with Crane using Docker Compose. First of all, make sure to install Docker and Docker compose.

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Crane 1.0.0 released!

on February 4, 2025

Publishing is an integral part of the data analysis process. Whether it’s in the form of code, reports or technical documentation, at some point artifacts need to be shared. More often than not, such artifacts are confidential and their access needs to be properly secured. There exist solutions for at least some types of artifacts, but we needed one simple tool that could help us with all the use cases we encounter in our daily practice, built with modern technology and security standards.

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Technologies

  • R
  • Python
  • Julia
  • Spark
  • Rust
  • Go
  • Java
  • Docker
  • Kubernetes