> For the complete documentation index, see [llms.txt](https://help.daasity.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.daasity.com/core-concepts/ai-analyst/ask-in-daasity.md).

# Ask in Daasity

## Ask in Daasity

The in-app AI Analyst is a chat assistant built into Daasity. Ask a question in plain language and it answers using your governed Daasity metrics - the same definitions behind your dashboards and Explores. No SQL, no report requests, no waiting on an analyst for a quick number.

### Getting started

Open AI Analyst from your Daasity workspace. You'll see **"How can I help you today?"** and a set of example questions. You can click one to run it, or type your own question in the box at the bottom.

Example starters include:

* *Top 10 products by revenue last 30 days*
* *Revenue by channel last 90 days*
* *Daily revenue trend this month*
* *New vs. returning customers*

Press **Enter** to submit, or **Shift+Enter** to add a new line. Ask in everyday language - you don't need to know table or field names.

### What an answer looks like

As it works, AI Analyst shows what it's doing - finding the relevant fields, then running the query - so the process is transparent. The answer itself is written in plain English and typically includes:

* **A clear summary** with the headline result called out (for example, the top product with its revenue and units), followed by a ranked breakdown.
* **A short insight** interpreting the numbers - concentration, trends, or risks worth noticing.
* **Assumption and caveat notes** flagged inline. For instance, if you ask for "last 30 days," it may note that it used the closest standard window (such as the latest 4-week period) and call out anything excluded. These notes are there so you can trust exactly what was measured.
* **View data.** Click **View data** under any answer to expand the underlying rows behind the response.

Because answers come from your governed semantic layer, the numbers line up with the rest of Daasity.

### Digging deeper

Under an answer, open **Dig deeper?** for suggested follow-up questions tailored to what you just asked (for example, "Which retailers are driving this product's sales?"). Click one to run it, or simply type your own follow-up in the box - the assistant keeps the context of your conversation within the thread.

### Working with threads

Each conversation is saved as a **thread** in the left panel under **Recents**, so you can return to a previous question or keep building on it. Start a fresh line of questioning any time with **New thread**, and use the search box to find an earlier conversation.

### Tips for good answers

* **Name the time frame** ("last 30 days," "this month," "Q2") - it removes ambiguity.
* **Name the dimension you care about** ("by channel," "by product," "new vs. returning").
* **Straightforward data pulls are the sweet spot** - a number, a ranking, or a trend comes back reliably.
* **Check the assumption notes** on the answer so you know exactly what was measured.
* **For analysis or opinions, keep it open-ended and iterate.** Ask follow-ups and sanity-check the result before you rely on it.

### Related tools in the workspace menu

The workspace menu (click your workspace name, bottom-left) includes helpers that support your analysis:

* **Query History** - revisit past queries.
* **Data Dictionary** - browse the models, metrics, and fields available to ask about.
* **Domains** - see the subject areas your questions can draw from.
* **Refresh Schema** - pull in recent changes to your data model.

### Prefer to use your own AI tool?

If you'd rather ask these same questions from Claude, Cursor, or another AI tool, [connect it to your Daasity data with MCP](/core-concepts/ai-analyst/connect-your-ai-mcp.md).