> For the complete documentation index, see [llms.txt](https://docs.syntho.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.syntho.ai/overview/get-started/syntho-bootcamp/5.-generators/ai-synthesize.md).

# AI synthesize

[AI synthesize](/configure-a-data-generation-job/configure-column-settings/ai-powered-generation.md) allows you to synthesize realistic data using machine learning models trained on your original dataset. This method maintains statistical fidelity while ensuring privacy and unlinkability to the source records.

#### When to use

* To create synthetic datasets for machine learning or analytics
* When high statistical accuracy and maximum privacy are required
* To expand datasets while preserving original distributions

#### When not to use

* When working with multiple related tables
* When data consistency across systems is required
* When you need to be able to revert to original records
* If entirely new, unseen text values must be generated
* If the data needs to follow specific rules with 100% certainty​

The Syntho platform supports a wide variety of data types. Under the hood, Syntho uses an encoding scheme where each data type is mapped to one of the following encoding types.

| Data type                                                                                                      | Description                                  |
| -------------------------------------------------------------------------------------------------------------- | -------------------------------------------- |
| [Discrete](/configure-a-data-generation-job/configure-column-settings/ai-powered-generation.md#discrete)       | Numerical counts (e.g. number of visits)     |
| [Continuous](/configure-a-data-generation-job/configure-column-settings/ai-powered-generation.md#continuous)   | Continuous values (e.g. weight, temperature) |
| [Categorical](/configure-a-data-generation-job/configure-column-settings/ai-powered-generation.md#categorical) | Predefined values (e.g. blood type, country) |
| [Datetime](/configure-a-data-generation-job/configure-column-settings/ai-powered-generation.md#datetime)       | Timestamps and dates (e.g. created at)       |

#### Interactive guide: How to apply AI synthesize

Follow the interactive guide below to apply AI synthesize.

{% embed url="<https://www.guidejar.com/guides/4ebdd966-24fe-4c67-b1a4-2ec1690d8c41>" %}

#### [Rare category protection](/configure-a-data-generation-job/configure-column-settings/ai-powered-generation.md#rare-category-protection)

To protect privacy, Syntho can automatically replace infrequent values in categorical columns:

* Threshold: minimum frequency before a value is considered rare (default = 10)
* Replacement: value used to replace rare categories (default = `*`)

#### [Advanced settings](/configure-a-data-generation-job/configure-column-settings/ai-powered-generation.md#advanced-settings)

[Generator-level](/configure-a-data-generation-job/configure-column-settings/ai-powered-generation.md#advanced-generator-settings)

* Max rows used for training: limit data for faster performance
* Take random sample: randomly sample rows for training

[Column-level](/configure-a-data-generation-job/configure-column-settings/ai-powered-generation.md#advanced-column-settings)

* Clipping thresholds: restrict extreme values in numeric/date columns
* Locale: set language model context for text/PII


---

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