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

# Retention and deletion

> See which records expire, what deletion removes and what can remain.

## Retention depends on the record

| Data                                                        | Current application behavior                                                                                                                                    |
| ----------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Production traces and their check evidence                  | A 30-day window measured from trace ingestion. Expiry uses the same deletion path as manual trace deletion, including explicitly derived saved cases.           |
| Application test reports                                    | Scheduled deletion after 30 days from report creation. Active tests are excluded until they finish.                                                             |
| Imported connector evidence                                 | Defaults to 30 days, with a configured range of 1–365 days. Overlapping synchronization preserves the original expiry rather than extending it on every import. |
| Independently saved documents, datasets, cases and criteria | No universal 30-day lifetime. They remain until removed or until an applicable source-specific retention period expires.                                        |
| Evaluation history and billing records                      | Aggregate scores, run metadata and accounting records can remain after detailed evidence is erased. The 30-day trace window is not their retention policy.      |
| Local exports and upstream originals                        | Removing a Bench record does not remove files you exported or data held in its original application.                                                            |

Deletion runs in the background. Active tests may need to finish before their
linked evidence can be removed. Exported files and copies in your own application
are outside Bench's deletion controls.

## Delete a production trace

Open **AI systems → your system → Production**, inspect the trace and choose
**Delete trace**. Read the confirmation before proceeding.

Deleting a trace erases the trace, its spans and checks, and saved test cases that
explicitly record that trace as their source. It also erases affected context
snapshots and associated detailed evaluation artifacts. This can remove more than
the visible trace because a summary or saved result may contain the same evidence.

A minimal deletion marker prevents delayed ingestion retries from restoring the
same trace identity. New, separately identified events are separate records. Cases
copied manually without the original trace reference are not automatically located
by content similarity. Review those copies separately.

Trace expiry follows this same provenance-based path. A case explicitly derived
from a trace can therefore expire with the source trace. Do not assume that adding
an incident to the library makes its original production payload permanent.

## Remove context, datasets or connections

Use **Manage sources** to remove selected saved context. Source removal deletes
its active and historical evidence, marks affected snapshots as erased and clears
associated detailed run artifacts and reusable scoring-cache entries. Aggregate
historical scores remain; erased evidence must not be presented as available for
reinspection or reuse.

Deleting a dataset also removes test-library cases linked to that dataset and
applies source erasure to those cases. Disconnecting an imported-source connector
removes its connection and associated evidence and applies the derived-artifact
cleanup. It does not delete the upstream project's original data.

Because runtime evidence or future automatic-run settings may embed removed
context, source erasure also removes the system's saved runtime reports and
automatic-runtime configuration, and clears retained hosted-job content. Configure
a new suite using the remaining approved context before enabling automatic testing
again.

Relevant queued/running work or unsettled evaluation reservations can block these
operations. Finish or cancel the work, allow reservation settlement, then retry.
A blocked deletion must not be interpreted as a completed erasure.

## Remove an AI system

Deleting a system removes its structure, context and attached datasets, and scrubs
its detailed evaluation artifacts before retaining aggregate run history. Runtime
records attached to that system are also removed or cleared. Minimal discovery
markers prevent the same explicitly deleted static system from being recreated
by the next scan.

Raw production traces belong to a repository and branch. Deleting a system does
not itself delete every trace from that repository; delete those traces separately
or allow their retention process to run. It also does not delete the source
repository or revoke the GitHub App installation. **Manage GitHub access** opens
GitHub's installation settings when you need to change that access.

## Backups and account deletion

Deleting a record removes it from the live application through the applicable
deletion process. Backup expiry is separate. Contact Bench for account-wide deletion
or contractual retention requirements.

See [security and privacy controls](/guides/security-and-privacy) to collect less data.