> For the complete documentation index, see [llms.txt](https://docs.ngsurvey.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ngsurvey.com/ai-suite/artemis-ai-agent/synthetic-respondents.md).

# Synthetic Respondents

Using the synthetic related prompts you can ask Artemis to create respondents based on criterias that you specify. Synthetic respondents can be very handy for testing or to simulate real world results  based on your AI knowledge.

{% hint style="info" %}
Depending on your AI provider you may hit limitation in the number of synthetic respondents that you can create at one time as some AI provider restrict the data amount even if you're on pay plan. 
{% endhint %}

Here a few samples prompts that you could use to create or manage style themes.

### 📊 Basic Dataset Generation

* “Generate 100 synthetic respondents for this survey.”
* “Create 100 synthetic responses with a balanced distribution across answer options.”
* “Simulate 50 respondents with realistic variation based on European male over 50 in pharma industry. Use your knowledge and statistics to generate real world results.”
* “Generate sample data for all questions so I can preview reports.”

### 📈 Distribution & Sentiment Control

* “Generate 100 respondents with generally high satisfaction scores.”
* “Simulate responses with mixed sentiment and moderate NPS.”
* “Create mostly positive responses with a small group of dissatisfied outliers.”
* “Generate data reflecting low satisfaction and declining trend.”

### 🎯 Targeted Scenarios

* “Simulate responses for a product launch survey with strong early adopters.”
* “Generate synthetic employee feedback with moderate engagement levels.”
* “Create customer feedback responses with varied satisfaction across services.”
* “Simulate a churn-risk scenario with declining satisfaction scores.”


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