I have documents in multiple file formats and I need a single, consistent Markdown output to feed into my LLM pipeline.

Convert documents from multiple file formats into a single, consistent Markdown output for downstream processing. This helps you standardize ingestion and reduce formatting-related failures in your LLM pipeline.

This feature produces a consistent Markdown representation from documents that may originate in different file formats. It is designed for LLM pipelines where having one predictable text format simplifies indexing, chunking, and prompt construction. You provide a document as input, and the output is normalized into Markdown so your pipeline can treat every document the same way. A consistent structure makes it easier to apply the same parsing rules across sources without building format-specific handlers. Standardized Markdown also improves reproducibility by reducing variability caused by inconsistent document formatting. This approach supports building reliable preprocessing steps like section detection, metadata extraction, and stable chunk boundaries. It can be used for knowledge base ingestion, RAG workflows, document summarization, and compliance archives that need consistent text outputs. By converging on Markdown, teams can iterate faster on prompts and retrieval logic without continually adapting to new input formats. Overall, the feature reduces ingestion complexity and makes document handling more predictable at scale.