> For the complete documentation index, see [llms.txt](https://docs.flashback.tech/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.flashback.tech/flashgate-platform/organization/statistics.md).

# Statistics

The **Statistics** section gives organizations deep observability across infrastructure, AI usage, private chat activity, and policy events.

## What you can analyze

### Gateway and resource usage

Track platform-wide and scoped metrics, including:

* credit consumption,
* AI/LLM usage,
* storage and data transfer,
* uploaded and downloaded data volume,
* token usage and trend comparisons over time.

### Private Chat analytics

Review how teams use private chat:

* activity levels,
* conversation and prompt volume,
* token consumption over time,
* workspace/repository distribution.

### Policy analytics

Admins can inspect policy-level signals such as:

* policy trigger counts,
* violation/breach indicators,
* risk trends,
* affected scopes and users.

This helps security and governance teams refine AI safety posture.

## Why this section is critical

Statistics convert raw operations into decisions:

* optimize infrastructure and provider mix,
* detect anomalies early,
* tune policies with evidence,
* and improve cost predictability.

## API mapping

See: [Statistics API](/support-reference/platform-api-reference/statistics.md)


---

# 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 dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.flashback.tech/flashgate-platform/organization/statistics.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.