I need structured JSON from my files so I can feed them into an LLM pipeline without writing custom parsers for each format.

This feature converts files into structured JSON so they can be used directly in an LLM pipeline. It reduces the need to build and maintain custom parsers for every input format, making ingestion more consistent and automation-friendly.

This feature produces structured JSON outputs from your source files so they can be reliably ingested by an LLM pipeline. It focuses on standardizing extracted content into a predictable JSON structure, which helps downstream steps like chunking, embedding, retrieval, and prompting. By removing the need to write bespoke parsers for each file type, it reduces engineering effort and ongoing maintenance. It also supports more consistent handling of mixed-format corpora, where documents may vary in structure and quality. The JSON output can be stored, versioned, and reprocessed, enabling reproducible experiments and easier debugging when pipeline results change. This approach helps you integrate new data sources faster because the pipeline expects one structured representation instead of many ad hoc ones. It can be used to prepare knowledge bases, internal documentation archives, contract repositories, research libraries, or customer support content for LLM-enabled applications. The end result is a simpler ingestion layer that improves reliability, portability, and scalability for LLM workflows.