Streamline your data pipelines to support real-time decision-making capabilities. Deploy best practices across your Big Data stack.

  • Prototype Development

    An iterative approach through quick proof-of-concepts will help validate your Big Data innovations faster than a waterfall approach.

  • Repeatable Deployments

    Go from Jupyter Notebooks to Cloud-native containers. Automate the delivery of your pipeline using Continuous Integration/ Continuous Deployment (CI/CD). Prevent drift in your architecture using Infrastructure as Code (IaC) tools like Terraform.

  • Observability

    Improve your ability to troubleshoot issues, and find performance bottlenecks by adding instrumentation in your ETL process. Roll up the data into dashboards for real-time decision making.

  • Data Pipeline Optimization

    Simplify and modernize your data pipeline: move away from batch processing and implement real-time streaming into your data lake.


End-to-End Quality

Professional methods and tools to ensure robustness, dependability, functional safety, cybersecurity and usability:

  • Agile process
  • CI/CD
  • DevOps pipelines
  • Secrets management
  • Source control management
  • Automated testing
  • Documentation
  • Instrumentation
  • Monitoring

Technology Expertise

20+ years of software development and deployment experience with a focus on:

  • Python
  • Django
  • Flask
  • Plone
  • React
  • PostgreSQL
  • Redis
  • Docker
  • Salt
  • Terraform
  • AWS
  • GCP

How to Engage with Us

Project 5

Can we help you?

Vision Builder

Getting on the same page

Strategic Planning

Why? What? How? When? How much?

High Performance Delivery

Rapid Development

Maintenance and Support

Scheduled and unexpected

Skill Up

Training and mentoring


Past Projects

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Projects

Latest Blog Posts

Plone Connection Podcast Ep. 01 — Philip Bauer

This month, our guest is Philip Bauer, a Plone-core developer and author of the Mastering Plone training. Philip is also the founder and owner of Starzel.de. Kim and Philip discuss their history with Plone, the past and the future of the Plone Conference, as well as Plone trainings.

4 Reasons to go with Python over ${language}

“Use the right tool for the job” is a golden rule of engineering. Working on software, however, there are often dozens of different languages that can get the job done. How can you know which one constitutes the right tool for the job?


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