> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cekura.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# A/B Testing

> Compare two versions of your agent side-by-side to measure prompt, model, or configuration changes.

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<CopyPageButton />

## Overview

A/B testing on Cekura lets you compare two (or more) runs of your agent against the same set of evaluators — so you can see whether a prompt change, model swap, or configuration tweak actually improves behavior before shipping it.

The flow is simple:

1. Run the same set of evaluators against **Version A** of your agent.
2. Make your change (update the prompt, switch the model, adjust tools, etc.).
3. Run the **same** evaluators against **Version B**.
4. Select both runs on the Results page and compare metric-by-metric.

<Note>
  Always run both versions against the **same evaluators** with the **same test profile**. Otherwise you're measuring noise from different test inputs rather than the change itself.
</Note>

## Prerequisites

Before running an A/B test, make sure you have:

* An agent configured on Cekura — see the [Testing Overview](/documentation/guides/testing-agents/overview) for the basic testing flow
* A stable set of evaluators that pass reliably for your baseline — see the [Suggested Testing Approach](/documentation/guides/testing-agents/suggested-testing-approach)
* A clear hypothesis about what you expect the change to improve (pass rate, latency, adherence to a specific metric, etc.)

## Running an A/B Test

<Steps>
  <Step title="Run Version A (baseline)">
    Select your evaluators and run them against your current agent configuration. Wait for the run to complete and record the run name or ID.
  </Step>

  <Step title="Apply your change">
    Update the agent's prompt, model, voice, tool configuration, or any other parameter you want to test. Change **one variable at a time** — otherwise you won't know which change caused the difference.
  </Step>

  <Step title="Run Version B">
    Run the **same evaluators** against the updated agent. Use the same test profile, personalities, and frequency so the only difference between the two runs is your change.
  </Step>

  <Step title="Select both runs and compare">
    On the Results page, select the checkboxes next to both runs and click **Compare**. Cekura shows a side-by-side breakdown of every metric and evaluator across the two runs.

    Look for:

    * **Overall pass rate** — did B improve or regress?
    * **Per-metric deltas** — which specific metrics moved, and by how much?
    * **Individual evaluator diffs** — open any evaluator to see the transcripts side-by-side and read why one passed and the other failed.
  </Step>
</Steps>

## Best Practices

### Change One Variable at a Time

If you change the prompt **and** swap the model in the same run, you can't attribute any improvement (or regression) to either change. Test changes in isolation.

### Use Frequency > 1 to De-Noise

Voice agents are non-deterministic. A single run can pass or fail by chance. Set frequency to 3–5 so each evaluator runs multiple times — the aggregate result is far more reliable than any single call. See [Load Testing](/documentation/guides/testing-agents/load-testing) for how frequency works.

### Keep the Test Set Fixed

Don't add or remove evaluators between A and B. If you want to expand coverage, do that first, re-establish the baseline, and then run the A/B test.

### Compare More Than Pass Rate

Two runs can have the same pass rate while differing dramatically on latency, talk ratio, or a specific workflow metric. The compare view surfaces all of these — don't stop at the headline number.

## Related Resources

* [Testing Overview](/documentation/guides/testing-agents/overview) — Run your first evaluators
* [Suggested Testing Approach](/documentation/guides/testing-agents/suggested-testing-approach) — Build a reliable evaluator suite
* [Load Testing](/documentation/guides/testing-agents/load-testing) — Use frequency to run each evaluator multiple times
* [Metrics Overview](/documentation/key-concepts/metrics/overview) — Understand what each metric measures