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add snippets to dashboards AI section #820

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add snippets to AI section
fiquick Oct 1, 2025
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Update ai-dashboards.adoc
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13 changes: 13 additions & 0 deletions modules/ROOT/pages/dashboards/ai-dashboards.adoc
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Expand Up @@ -11,6 +11,9 @@ When creating a dashboard with AI, the AI analyzes your link:https://neo4j.com/d
It cannot read the actual data in your database.
====

The intelligent prompting happens in the background.
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@rsill-neo4j rsill-neo4j Oct 6, 2025

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The intelligent prompting happens in the background.
The prompt is processed in the background.

AI is going to analyse the schema, and it will try to make up some questions, and then it will convert each of these questions into a chart.
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AI is going to analyse the schema, and it will try to make up some questions, and then it will convert each of these questions into a chart.
The AI analyzes your database schema and tries to come up with useful queries about the data while taking your prompt into account.
Then it creates a suitable visualization for each query.


If you do not enter a prompt, Neo4j AI will still make use of your database schema and come up with a suitable dashboard.

Note that the following examples might differ when you reproduce them.
Expand Down Expand Up @@ -79,4 +82,14 @@ image::dashboards/ai-dashboard-dual-focus-1.png[]
.A dashboard with both a data and a visualization focus (2)
image::dashboards/ai-dashboard-dual-focus-2.png[]

== Quality of the data model

AI provides a great starting point, but the quality of your underlying data model still matters.
A graph model that has been thought out well, leads to a dashboard that tells more meaningful stories.
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A graph model that has been thought out well, leads to a dashboard that tells more meaningful stories.
A graph model that has been thought out well leads to a dashboard that yields more meaningful insights.

AI infers nodes and relationships, but you might like to refine the model based on your specific questions - that way you will be able to reference entities directly from your schema (like `Customer`, `Order`, or `Category`) to guide AI towards more relevant charts.
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This sounds more like prompt writing tips - using the exact entity names in a prompt to make it easy for the AI to interpret the prompt.

in general i don't think that the actual data model is something that is influenced too much by what kind of dashboards we can build from it, but rather how the data should be modeled so they can be processed efficiently.

I'd say this section could instead be about making sure the prompt aligns with the data model?


== AI as a starting point

Remember, you can always edit an AI-generated dashboard.
It's fun to use AI as a starting point, and then build on it by editing the output - and refining visualizations, colors, and layouts to match your needs.
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It's fun to use AI as a starting point, and then build on it by editing the output - and refining visualizations, colors, and layouts to match your needs.
It is a valid workflow to use AI as a starting point, and then build on it by editing the output - and refining visualizations, colors, and layouts to match your needs.