> For the complete documentation index, see [llms.txt](https://docs.taloflow.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.taloflow.ai/security/platform-controls/evaluation-data-retention.md).

# Evaluation Data Retention

How long evaluations are kept, who owns the data, and export options.

### Data availability and retention

This page covers retention of **evaluation data and exports**. For **platform logs, audit logs, and backups**, see [Logs, Audit Logs, and Backups](/security/platform-controls/logs-audit-logs-and-backups.md).

#### Evaluation Retention Period

Completed evaluations remain available in Taloflow for **12 months** from the evaluation completion date.

Use this window to:

* Access and review evaluation results
* Generate additional reports
* Export data in various formats
* Share findings with stakeholders

After the 12-month period, availability is not guaranteed. Contact Taloflow before expiry if you need extended access.

#### Data Ownership

You retain ownership of your:

* Evaluation results and analyses
* Exported reports (PDF, Excel)
* Custom configurations
* Rating methodologies
* Vendor assessments

#### Export Capabilities

You can export evaluation outputs at any time:

* [Export to PDF](/data-export/export-to-pdf.md)
* [Export to Excel](/data-export/export-to-excel.md)

Exported files remain your property. Access to Taloflow does not affect your copies.

#### Extended Retention

If you need retention beyond 12 months, contact us to discuss options:

* [Support Hub](broken://spaces/-MQkUmzRViVxDERN9vKk/pages/7w2btLpaU63hhnW4Dd7q)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.taloflow.ai/security/platform-controls/evaluation-data-retention.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.