Compare custom models in Microsoft Syntex
Use the following table to see differences in custom models to help identify the most appropriate model to use for your needs.
| Feature | Unstructured document processing | Freeform document processing | Structured document processing |
|---|---|---|---|
| Associated with this training method in the UI |  |
 |
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| Use for this type of content | Unstructured or semi-structured file formats, for example Office documents where there are differences in the layout, but still similar information to be extracted. | Unstructured and free-form file formats, for example documents that have no set structure such as letters, contracts, and statements of work. | Structured and semi-structured file formats, for example PDFs for forms content such as invoices or purchase orders where the layout and formatting is similar. |
| Model creation | Model created in SharePoint in a new site, the content center. | Model created in AI Builder with seamless access from SharePoint document library. | Model created in AI Builder with seamless access from SharePoint document library. |
| Classification type | Trainable classifier with optional extractors using machine teaching to assign document location on what data to extract. | Not applicable | Not applicable |
| Locations | Can be applied to multiple libraries. | Can be applied to multiple libraries. | Can be applied to multiple libraries. |
| Supported file types | Train on 5-10 .pdf, Office, or email files, including negative examples. Files are truncated at 64,000 characters. OCR-scanned files are limited to 20 pages. Supports more than 20 file types. See supported file types. |
Train on .pdf, .jpg, or .png format, total 50 MB and 500 pages. | Train on .pdf, .jpg, or .png format, total 50 MB and 500 pages. |
| Integrate with managed metadata | Yes, by training entity extractor referencing a configured managed metadata field. | No | No |
| Compliance feature integration with Microsoft Purview Information Protection | Set published retention labels. Set published sensitivity labels. |
Set published retention labels. Set published sensitivity labels. |
Set published retention labels. Set published sensitivity labels. |
| Supported regions | Available in all regions. | Relies on Power Platform. For information about global availability for Power Platform and AI Builder, see Power Platform availability. | Relies on Power Platform. For information about global availability for Power Platform and AI Builder, see Power Platform availability. |
| Transactional cost | For pay-as-you-go licensing, see pricing. For per-user licensing, not applicable. |
For pay-as-you-go licensing, not applicable. For per-user licensing, uses AI Builder credits. 3,500 credits are included for each Syntex license per month. One million credits allow processing of 10,000 file pages. |
For pay-as-you-go licensing, not applicable. For per-user licensing, uses AI Builder credits. 3,500 credits are included for each Syntex license per month. One million credits allow processing of 10,000 file pages. |
| Capacity | No capacity restrictions. | Uses the default Power Platform environment (custom environments with Dataverse database supported). | Uses the default Power Platform environment (custom environments with Dataverse database supported). |
| Supported languages | Supports more than 40 languages. | Supports more than 40 languages. | Supports more than 100 languages. |