ZenML GmbH

MLOps and LLMOps workflow automation tools for ZenML users

Guided implementation of ZenML MLOps best practices including metadata logging, experiment tracking, alerters, scheduling, secrets management, and Model Control Plane setup

Scope and decompose ML workflow ideas into realistic ZenML pipeline architectures through an in-depth interview process

Author ZenML pipelines with steps, artifacts, Docker settings, materializers, metadata logging, secrets management, YAML configuration, and custom visualizations

Migrate Apache Airflow DAGs and workflows to idiomatic ZenML pipelines with concept mapping, code translation, and unsupported pattern flagging

Migrate Databricks Workflows (Lakeflow Jobs) to idiomatic ZenML pipelines with concept mapping, notebook refactoring, code translation, and unsupported pattern flagging