> ## Documentation Index
> Fetch the complete documentation index at: https://braintrust.dev/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Run experiments in the UI
> Evaluate prompts and workflows in the Braintrust UI, with no code or local setup required.
Create and run experiments in the Braintrust UI without writing code. Build one from scratch with a dataset and scorers, or promote a playground run you've iterated on to an immutable snapshot.
## Create from scratch
1. Go to [** Experiments**](https://www.braintrust.dev/app/~/experiments).
2. Click **+ Experiment** or use the empty state form.
3. Select one or more tasks to evaluate: prompts, workflows, or [remote evals and sandboxes](/docs/evaluate/remote-evals).
4. Choose or create a dataset:
* **Select existing dataset**: Pick from datasets in your organization
* **Upload CSV or JSON**: Import test cases from a file
* **Empty dataset**: Create a blank dataset to populate manually later
5. Optional: Click **Filter** under the dataset field to scope the experiment to a subset of records. Filter by `input`, `expected`, `metadata`, `tags`, or any custom column using SQL expressions. The experiment runs only against records matching the filter, and the filter is recorded on the experiment.
6. Use the **Scorers** field to add [scorers](/docs/evaluate/write-scorers) and [classifiers](/docs/evaluate/write-scorers#classifiers) to score and label outputs.
7. Click **Create** to execute the experiment.
UI experiments run without a time limit on cloud and on self-hosted deployments running data plane v2.0 or later.
## Promote from a playground
Playground runs are mutable — re-running overwrites previous results. When you've iterated to a configuration worth keeping, promote it to an experiment to capture an immutable snapshot:
1. Run your playground.
2. Select **+ Experiment**.
3. Name your experiment.
4. Access it from the [** Experiments**](https://www.braintrust.dev/app/~/experiments) page.
Each playground task maps to its own experiment. Experiments created this way are comparable to any other experiment in your project.
## Next steps
* [Interpret results](/docs/evaluate/interpret-results) from your experiments
* [Compare experiments](/docs/evaluate/compare-experiments) to measure improvements
* [Run experiments in code](/docs/evaluate/run-in-code) with the SDK
* [Run experiments in CI/CD](/docs/evaluate/run-in-ci) to catch regressions automatically