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Simulation

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The most common type of execution is a Simulation - used to execute analytics contained in the definition of an object that has been registered in the platform. And additionally, run dashboards and reports on that output.

A Simulation task typically involves:

  • Current object: Object which is currently selected and being tested. This can be a Pipeline, Model, RAG, or Prompt.
  • Data Source: The data to run the object on.
  • Report & Metrices: Exact evaluation metrics to be run on the output.

How to run a Simulation Task?

Section titled “How to run a Simulation Task?”

  • Register the object on the platform.

  • Go to the Details page of an object to be compared and click on the Run -> Simulation button.

  • Provide description about the run.

  • Select Dashboard to be evaluated in Dashboard Selection.

  • Prepare the data in Data Sources which will be used for evaluation.

  • Click on Run at the bottom and wait for job completion.

    • Once a job has been submitted it starts in the NEW status
    • The job will go through the following statuses: COMPILING > QUEUED > RUNNING and finally stop at COMPLETED of FAILED

All simulation tasks are systematically recorded on the platform and displayed on the Jobs page of an object in a structured format. They can also be exported as part of the automated documentation process.

Note: The platform allows customizing reports and dashboards specifically for simulation tasks. Note: Corridor allows running jobs in parallel and multiple threads at a time within a job to expedite the evaluation process.

Validating an evaluator

Section titled “Validating an evaluator”

Simulation is also how you check that an evaluator can be trusted. An LLM-as-a-judge is itself a registered model, so you can run it over a ground-truth dataset and compare its verdicts against the known answers — computing classification metrics just as you would for any model. The same applies to a whole report: run it on labelled data with expected outputs and confirm the numbers and visuals come out as intended before relying on it in monitoring. These runs can then be attached to the object’s Approval Workflow as validation evidence.