After partitioning, you can have a vision language model (VLM) optimize the fidelity of text blocks that Unstructured initially processed during its partitioning phase. Here are a few examples of Unstructured’s output of text blocks that were initially processed, and the more accurate version of these text blocks that were optimized by using Claude Sonnet 4. Irrelevant lines of output have been omitted here for brevity. Example 1: Vertical watermarked textDocumentation Index
Fetch the complete documentation index at: https://docs.unstructured.io/llms.txt
Use this file to discover all available pages before exploring further.



Improve text fidelity with generative OCR
To have Unstructured perform generative OCR optimization, do the following:- For Unstructured UI users, add an Enrichment node of type Generative OCR to an Unstructured custom workflow.
- For Unstructured API users, add a Generative OCR task.
You add this task as either as an object in a
workflow_nodesarray (for curl) or as aWorkflowNodein aWorkflowNodescollection (for Python). This object or collection applies whenever you create a workflow, update a workflow, or create an on-demand workflow job.

