Advanced Data Science
& Engineering Support

To help teams succeed with AI projects based on advanced machine learning, we provide a support concept that combines expert advisory with the possibility to get hands-on help from data scientists and data engineers. The service is not tied to any particular platform, our experts will help with anything that falls within our core areas of expertise.
Our core areas of expertise
AI and machine learning
Our philosophy for ML/AI encompasses both the exploratory stages of model development as well as the processes needed to bring trained models to production services. This is why we advocate solutions that are built ground up to support flexible experimentation, high-performance training, and to let continuous delivery meet analytics. We specialize on open source software stacks and we are proponents of the Kubeflow initiative.
Cloud native computing
We are passionate about creating cloud native and vendor agnostic applications based on leading open source software stacks on top of Kubernetes, OpenShift and OpenStack. With our background in scientific computing, we know the importance of designing ground up for high performance and scalability. Automation is key to sustainable solutions, and this is why infrastructure as code is one of our core focus areas.
Data science & engineering
It all starts with data, and no machine learning project will succeed without sound principles for scientific data management. In fact, good data engineering practices is key to a unlocking long term business value from machine learning. Our team is highly experienced in solutions for secure, fast and highly scalable data analysis. We are specialized on connecting data science with the DevOps culture, using automated and repeatable data pipelines built on open source software stacks.
Scientific computing & HPC
Our experience in scientific computing spans the range from data-driven modeling to simulation to optimization. The fact that we have extensive experience with both traditional HPC and cloud computing makes us an ideal partner when developing performance critical applications leveraging cloud infrastructure, and when developing hybrid infrastructure tailored to meet both the needs for flexibility and performance posed by cloud native scientific computing applications.
Typical things that you can get help with:

Selection of machine learning methods
Advice on data preprocessing, feature engineering, dimension reduction etc.
Continuous analytics
Scientific data management
Architecture of highly scalable workflows and pipelines for batch and streaming data
Cloud strategy, vendor-and technology assessment
Feedback on project plans
Code reviews, troubleshooting
Infrastructure automation, configuration management, DevOps
Microservices, Kubernetes
Service tiers
We offer our services by charging a fixed monthly fee to guarantee convenient access to our expert advisory service. When you need limited-scope hands-on help from our data scientists, data engineers and cloud architects, you can add developer time in 0.1 FTE chunks at a fixed, predictable cost.

We offer the service plan in two tiers that you can switch between from month-to-month.
  • Answers to expert advisory requests within 24h on business days (email)
  • Up to 2 hours of face-to-face video meetings with expert advisors/month (access within 5 business days)
  • Access to hands-on help at a flat rate of 20000 EUR/FTE/month
1000 EUR / month
Like standard, and in addition:
  • Dedicated contact person
  • Live chat with the engineering team (business hours)
  • Up to 6 hours of face-to-face video meetings/month (access within 2 business days)
  • Up to 10h of limited scope junior and mid-senior hands-on help (code reviews, troubleshooting, containerization, automation, piloting etc.). Rolls over to next month if not used.
  • Access to additional hands-on help at a flat rate of 15 000 EUR/FTE/month (same month)
3500 EUR / month
Your AI strategy
Our advanced support service is specifically designed to address the four most important points related to an AI strategy:
Reduce risk with an open-source centric AI strategy
By ensuring that you have continuous access to leading data engineers and cloud native experts that live and breathe open source.
Enable a quick project start and an agile approach
By putting our experts on your team, there is no need to decide on a particular cloud infrastructure or a firm technological roadmap before getting started with your project. We will make sure that you arrive at a sustainable solution no matter where the evolving requirements take you.
Retain ownership of your AI projects
Being assured that you have continuous access to experts and engineering capacity to overcome technological roadblocks, even resource- and knowledge constrained teams can take full ownership of AI projects.
Avoid vendor lock-in
The strategic choice of cloud infrastructure providers and data-asset ownership should not be taken on the basis of availability of particular ML tools. Our expert team will help you with a cloud native strategy to ensure that your AI solutions are vendor agnostic.