I have documents in different file formats, and I need a consistent Markdown version for my LLM workflow.

This feature standardizes documents from different file formats into a consistent Markdown output. It helps you keep formatting predictable and improves reliability when using documents in LLM prompts, retrieval, or downstream processing.

This feature converts documents from various file formats into a consistent Markdown representation for use in an LLM workflow. It focuses on producing a predictable structure so you can reuse the same parsing, chunking, or indexing steps across sources. You can use it to normalize incoming files before sending content to an LLM, storing it in a knowledge base, or preparing it for retrieval-augmented generation. A consistent Markdown output makes headings, lists, tables, and code blocks easier to identify and process. It also reduces manual cleanup when documents come from multiple tools or teams with different formatting conventions. This standardization helps improve the quality of citations, summaries, and extracted fields by keeping document layout more uniform. It is useful for building repeatable pipelines where document ingestion needs to be automated and reliable. It can also support workflows that compare versions, track changes, or run quality checks by using one common text format. Overall, it simplifies document preparation and makes downstream LLM behavior more consistent across inputs.