ZenML 0.80.0 transforms tenant structures into workspace/project hierarchies with advanced RBAC for Pro users, while enhancing tagging, resource filtering, and dashboard design. Open-source improvements include Kubernetes security upgrades, SkyPilot integration, and significantly faster CLI operations. Both Pro and OSS users benefit from dramatic performance optimizations, GitLab improvements, and enhanced build tracking.
Manual EU AI Act compliance is unmanageable. This credit scoring pipeline shows how ZenML transforms regulatory requirements into automated workflows—from bias detection and risk assessment to human oversight gates and Annex IV documentation.
Traditional banks face growing pressure to deploy machine learning rapidly while meeting strict regulatory requirements. This blog post explores how modern MLOps practices, like automated data lineage, validation testing, and model observability can help financial institutions bridge the gap. Featuring real-world insights from NatWest and an open-source ZenML pipeline, it offers a practical roadmap for compliant, scalable AI deployment.
Future-proof your ML operations by building portable pipelines that work across multiple platforms instead of forcing standardization on a single solution.
In this MLflow vs Weights & Biases vs ZenML article, we explain the difference between the three platforms and educate you about using them in tandem too.
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