--- title: "AI usage auditing" description: "See token and message counts, chat logs, and more." url: "https://www.metabase.com/docs/latest/ai/usage-auditing" version: "65" --- # AI usage auditing > AI usage auditing is only available on [Pro](https://www.metabase.com/product/pro) and [Enterprise](https://www.metabase.com/product/enterprise) plans (both self-hosted and on Metabase Cloud). _Monitor > AI auditing_ Admins can get an overview of human-robot interactions across Metabase, from high-level stats like total token counts down to visibility into actual conversations. These interactions include the in-product Metabot chat sidebar, Metabot conversations in [Documents](https://www.metabase.com/docs/latest/documents/start.md), [Slack chats](https://www.metabase.com/docs/latest/ai/metabot-slack.md), and [inline SQL editing](https://www.metabase.com/docs/latest/ai/metabot.md#inline-sql-editing). The usage auditing section includes: - [Usage stats](#usage-stats): aggregate charts across all Metabot activity. - [Conversations](#conversations): a filterable list of every conversation, with a detail view for each. You can also build your own questions on top of the [Usage Analytics views](#building-custom-reports) that back these reports. ## Usage stats _Monitor > Usage stats_ The Usage stats page shows aggregate Metabot activity over a date range you choose, defaulting to the previous 30 days. ### Filters - **Date range**: the time window the charts cover. - **User**: limit to a single person (or **All users**). - **Group**: limit to a single [group](https://www.metabase.com/docs/latest/people-and-groups/managing.md) (or **All groups**). - **Tenant**: limit to a single [tenant](https://www.metabase.com/docs/latest/embedding/tenants.md). Only shows up if tenants are enabled. ### Metrics Pick what you want to count: - **Conversations**: one row per distinct Metabot chat, across every surface listed above (chat sidebar, Documents, Slack, inline SQL). Not MCP conversations. - **Tokens**: total tokens (input and output) consumed by LLM calls. - **Messages**: every message exchanged, both from people and from Metabot. For each metric, you'll see the same set of charts: - **By time**: a time-series chart that buckets by hour or day depending on the date range you filter. Defaults to day. - **By source**: _where_ in Metabase the request came from. See [Sources and profiles](#sources-and-profiles). - **By profile**: _which_ Metabot persona answered. See [Sources and profiles](#sources-and-profiles). - **Users with most ...**, **Groups with most ...**, **IP addresses with most ...**: top-N rankings. - **Tenants with most ...**: only shown when tenants are enabled. You can drill through in the **By day**, **Groups with most ...**, **Users with most ...**, or **Tenants with most ...** charts to see the [Conversations list](#conversations) with the corresponding filter applied. The **By source**, **By profile**, and **IP addresses with most ...** charts are display-only. ## Sources and profiles - **Source** is _where_ the request came from in Metabase. - **Profile** is _which agent persona_ answered it. They often line up (a conversation that started in Slack is handled by the Slackbot profile), but they don't have to. A conversation started from the Metabot chat sidebar might be handled by the **Internal**, **NLQ**, or **SQL** profile depending on what the person asked. The Conversations admin page only shows **Profile**. Source is visible in the **Usage stats** charts and in the [Usage Analytics models](#building-custom-reports) used to build custom reports. ### Sources Each conversation is tagged with a source (where in Metabase the conversation took place). The **By source** chart in [Usage stats](#usage-stats) groups conversations by a human-readable `source_name`, and the [AI Usage Log](#building-custom-reports) model exposes both `source_name` and a raw `source` ID (like `metabot_agent`, `oss-sql-gen`, `document_generate_content`) for custom reports. Conversations Metabase couldn't classify show up as `(empty)` on the chart. | Source name | Where it comes from | | ------------------- | ----------------------------------------------------------------------------------------------------------------------- | | `Metabot` | The Metabot chat sidebar inside Metabase. | | `Documents` | Content generation inside [Documents](https://www.metabase.com/docs/latest/documents/start.md). | | `Suggested Prompts` | Background generation of suggested prompts. | | `Slackbot` | Conversations that started in [Slack](https://www.metabase.com/docs/latest/ai/metabot-slack.md). | | `SQL` | [Inline SQL editing](https://www.metabase.com/docs/latest/ai/metabot.md#inline-sql-editing) in the native editor. | | `Unknown` | A conversation Metabase couldn't classify (distinct from no-source conversations, which appear as `(empty)` on charts). | ### Profiles A profile is the configuration Metabot uses for a conversation: which prompt, which tools, and what it's allowed to do. The Conversations admin page, the **By profile** chart in [Usage stats](#usage-stats), and the **Metabot Conversations** model (see [Building custom reports](#building-custom-reports)) all show the human-readable profile name. The [AI Usage Log](#building-custom-reports) model exposes the raw `profile_id` instead (e.g. `internal`, `embedding_next`). | Profile | What it does | | ----------- | ------------------------------------------------------------------------------------------------------------------------- | | `Internal` | The default Metabot in the chat sidebar. Can build query-builder questions _and_ write SQL. | | `NLQ` | Natural-language querying only. Always returns a [query builder](https://www.metabase.com/docs/latest/questions/query-builder/editor.md) result, never SQL. | | `SQL` | SQL writing only. Used by [inline SQL editing](https://www.metabase.com/docs/latest/ai/metabot.md#inline-sql-editing) and similar surfaces. | | `Slackbot` | The persona behind [Metabot in Slack](https://www.metabase.com/docs/latest/ai/metabot-slack.md). | | `Embedding` | The Metabot persona used inside [embedded Metabase](https://www.metabase.com/docs/latest/embedding/start.md). | | `Documents` | Generates content inside [Documents](https://www.metabase.com/docs/latest/documents/start.md). | ## Conversations _Monitor > Conversations_ The Conversations page lists every Metabot conversation Metabase has on file, newest first. ### Filters - **Date range**, **User**, **Group**, **Tenant**: same as the [Usage stats filters](#filters). ### Columns Each row shows: - **User**: who started the conversation. - **Profile**: which Metabot persona answered. - **Date**: when the conversation started. - **Messages**: total messages, including both sides. - **Tokens**: total LLM tokens spent. - **Queries**: how many queries (SQL or query-builder) Metabot generated during the conversation. - **Searches**: how many search-tool calls Metabot made. - **IP**: the IP address the request came from. You can sort by Date, Messages, or Tokens. Click any row to open the [conversation detail](#conversation-detail). ## Conversation detail The detail view is a full audit of a single conversation. It includes: - **Header**: start date, the person who chatted with Metabot, the profile Metabot used, the person's groups (including whether they're an admin), and tenant if applicable. From the **...** menu next to the person's name you can jump to all of their conversations, or to their account details. - **Stat tiles**: Messages, Total tokens, Queries run, Searches. - **Feedback** (if any): thumbs-up or thumbs-down and comments. The agent response that triggered the feedback is shown alongside. - **Conversation transcript**: the full message-by-message exchange. Tool calls (search calls, query construction, etc.) are inlined. You can click "View" to open a modal with the info. - **Queries generated**: every SQL or [query builder](https://www.metabase.com/docs/latest/questions/query-builder/editor.md) (MBQL) query Metabot wrote during the conversation, with the referenced tables listed underneath. Hit **Visit** on a query to open the item in a new tab and run it yourself. ### The `/inspect` shortcut If you're an admin chatting with Metabot, type `/inspect` in the chat to jump straight from the current conversation to its detail page in Usage auditing. ## Building custom reports Three [Usage Analytics](https://www.metabase.com/docs/latest/usage-and-performance-tools/usage-analytics.md) models back the Usage auditing pages. - [AI Usage Log](https://www.metabase.com/docs/latest/usage-and-performance-tools/usage-analytics-reference.md#ai-usage-log): one row per LLM call. - [Metabot Conversations](https://www.metabase.com/docs/latest/usage-and-performance-tools/usage-analytics-reference.md#metabot-conversations): one row per conversation. - [Metabot Messages](https://www.metabase.com/docs/latest/usage-and-performance-tools/usage-analytics-reference.md#metabot-messages): one row per message. Save your custom questions in the [Custom reports](https://www.metabase.com/docs/latest/usage-and-performance-tools/usage-analytics.md#custom-reports-collection) sub-collection so the reports inherit the right permissions. ## What isn't tracked [MCP](https://www.metabase.com/docs/latest/ai/mcp.md) activity isn't included in Usage auditing. MCP requests don't go through Metabot's conversation pipeline, so they don't generate conversations or token rows. ## Further reading - [AI usage controls](https://www.metabase.com/docs/latest/ai/usage-controls.md) - [AI settings](https://www.metabase.com/docs/latest/ai/settings.md) - [Metabot](https://www.metabase.com/docs/latest/ai/metabot.md) - [Metabot in Slack](https://www.metabase.com/docs/latest/ai/metabot-slack.md) - [Usage analytics](https://www.metabase.com/docs/latest/usage-and-performance-tools/usage-analytics.md) - [Permissions overview](https://www.metabase.com/docs/latest/permissions/start.md)