Sorry, I think something’s got lost in translation here, but thanks for the explanation.

Hopefully this is clearer:

• Say we have a new ClearML pipeline as code on a new commit in our repo.
• We want to build and run this new pipeline and have it available on the ClearML Server.
• We want to run a suite of tests that validate/verify/etc the performance of this entire ClearML Pipeline, e.g. by having it run on a set of predefined inputs and checking the various artifacts that were created – these checks will be made from outside the ClearML Pipeline itself, i.e. we require the Pipeline Run to have been stored on ClearML and we require a Task ID to get the info.
• If validation is passed, we want to mark the ClearML Pipeline run, e.g. via a tag, as having passed the tests, such that our automated systems know how to find the correct ClearML Pipeline to clone for future runs.
  When you mention model verification and training, you are talking about those running within the pipeline. This is not the desired behaviour, as the Pipeline itself is the product and therefore the Pipeline itself needs, as a whole, to be validated/verified!