Automated testing for data, models, and notebook code. Reproducible, versioned, CI/CD-integrated.
Why DeepTest?
DeepTest closes the gap in quality assurance for AI systems. Machine learning projects often lack binding standards: data changes, models drift, and untested assumptions lead to regressions and uncertainty. Without uniform testing mechanisms, the reliability of AI systems remains difficult to verify and confidence in their results quickly dwindles.
DeepTest applies proven software testing principles to data, models, and code—with automated testing, clear versioning, and full traceability. This results in stable, verifiable ML pipelines that enable faster cycles, fewer errors, and greater confidence.
What can DeepTest do?
Ensuring data quality
DeepTest enables you to detect errors, gaps, or distortions in your training and test data at an early stage. This allows you to lay the foundation for reliable AI and machine learning models and avoid costly surprises later in the project.
Your advantage: Greater safety, better results—right from the start.
Making models reliable
DeepTest puts your AI models through their paces: weaknesses, risks, and unexpected behaviors are revealed before they become a problem. Robustness, accuracy, and bias are also analyzed to ensure true stability.
Your advantage: Maximum confidence in your AI – for stable, traceable decisions.
Securing code and processes
DeepTest keeps your AI code clean, efficient, and traceable. Automated linting checks, code metrics, and unit tests ensure that your MLOps processes are maintainable and auditable at all times.
Your advantage: Fewer errors, greater transparency—and always ready for audits.
Automated testing & innovation
DeepTest automatically creates new test cases for data, models, and code. By simulating rare scenarios and metamorphic transformations, your AI becomes more robust and remains reliable even when changes occur.
Your advantage: Innovation without risk – your AI grows with your requirements.
Continuous improvement
DeepTest allows you to keep track of all changes in your MLOps pipeline. Automated regression tests and version comparisons immediately show when quality deteriorates, enabling you to take targeted countermeasures and continuously optimize your machine learning models.
Your advantage: Sustainable quality and full control over your development.
Flexible integration
DeepTest adapts flexibly to your IT and MLOps landscape—whether cloud, on-premises, or hybrid. The solution grows with your requirements and can be seamlessly integrated into existing CI/CD pipelines and development processes.
Your advantage: Future-proof AI quality assurance that scales with your business.
How can I use DeepTest?
DeepTest integrates seamlessly into your existing MLOps environment. You can incorporate it into CI/CD pipelines to automatically execute data, model, and code tests. You can control approvals using defined quality metrics and release gates. Thanks to its modular architecture, DeepTest can be used for both new ML projects and existing workflows—locally, in the cloud, or in a hybrid setup. This means that quality assurance for AI becomes an accelerator rather than a hurdle.
Be there from the very beginning.
Sign up and get notified as soon as DeepTest launches in Q2 2026.
