> For the complete documentation index, see [llms.txt](https://docs.alkemi.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.alkemi.ai/documentation/basics/data-products/training-your-data-product/creating-automated-training-data.md).

# Creating Automated Training Data

The Automated tab leverages AI to generate synthetic training examples, accelerating the training process while maintaining quality through review mechanisms.

## Ways to generate training data

### 1. Quick Generation (Synchronous) 

Instantly creates up to 10 prompt/query pairs. Navigate to the Text to SQL Training tab in your Data Product and Click the **"Generate"** button.

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#### **What synchronous generation is best for**

Quick testing or when you need a few examples immediately.
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#### **Trade-offs**

Uses faster but lower-quality models due to speed requirements
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<figure><img src="/files/QZ2xI9RA73BLAztDZ8kg" alt=""><figcaption></figcaption></figure>

{% embed url="<https://www.loom.com/share/02394732fbc14c6783e9283dd534ebac?sid=e3d5d25a-7dd4-4258-a06e-2f8f89710ed8>" %}

### 2. Configured Generation (Asynchronous) - Recommended

Configures ongoing generation of synthetic queries.

* **Quantity**: Specify how many synthetic queries to generate in total
  * This number includes existing rows. If you have 5 rows already and set the
* **Auto-approval**: Choose whether queries should be:

  * Automatically approved and used immediately
  * Held in "pending" status for manual review

  <figure><img src="/files/3sjp4jTLTUYZccjR6t85" alt=""><figcaption></figcaption></figure>

#### **Configuration Options**

When setting up automated generation, consider:

* **Volume**: Start with smaller batches (between 5 and 20) to assess quality
* **Review requirements**: Initially, either enable manual review or set a high minimum certainty (between 80% and 95%) to ensure the quality of generated examples
* **Iteration**: Adjust configuration based on the quality of generated examples

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#### **Why asynchronous generation is preferred**

* Uses higher-quality AI models
* Includes additional validation steps
* Produces more accurate and relevant training examples
* Runs in the background without interrupting your workflow
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