Extract structured text, tables, headings, code blocks and images from PDFs, DOCX and HTML into clean LLM-ready Markdown.
Streamline Document AI and RAG ingestion pipelines by converting complex layouts into LLM-friendly formats.
Extract document structures, hierarchies, headings, bulleted lists, and blockquotes exactly as they exist in raw PDF or Office layouts.
Apply advanced OCR to read text in layout columns, embedded images, scanned docs, or hand-drawn schematics.
Convert complex visual grid tables, spreadsheets, and nested database grids into clean, readable Markdown syntax tables.
Strip unnecessary presentation tags, metadata, styles, and styling margins to lower LLM prompt token counts.
Convert text-heavy pages dynamically inside synchronous API requests, or batch process long PDFs with async webhook alerts.
Direct integration targets for document ingestion, retrieval-augmented generation (RAG) pipelines, and metadata indexing.
Define custom section rules or tag elements to split long text into semantically cohesive prompt context blocks.
Enterprise-grade data privacy. Your document data is processed in memory and never stored, indexed, or used for model training.
