I need structured JSON from documents so I can feed the content into an LLM pipeline without writing a custom parser for each file type.

Convert documents into structured JSON so you can reliably pass extracted content into an LLM pipeline. This removes the need to build and maintain custom parsers for each document type and keeps your ingestion workflow consistent across sources.

This feature outputs structured JSON representations of document content to support downstream LLM pipelines and automation workflows. It focuses on providing a consistent, machine-readable format that can be fed into chunking, embedding, retrieval, or prompt assembly steps. By standardizing output, you can ingest multiple document types without implementing a different parsing approach for each one. The resulting JSON can be used to preserve meaningful structure such as sections and text blocks, enabling better control over how content is indexed or summarized. This also helps reduce ingestion errors caused by inconsistent formatting and edge cases in source files. Teams can use the same JSON schema across projects to simplify integration testing and monitoring. It is useful for building searchable knowledge bases, extracting content for Q&A systems, and preparing corpora for fine-tuning or evaluation. It can also support compliance or auditing workflows where a structured, traceable representation of the original content is required. Overall, it streamlines document-to-LLM ingestion by producing predictable JSON output that is easier to validate, transform, and route through your pipeline.