Kami PDF Tool

Kami PDF Tool provides server-side PDF analysis for content teams, researchers, and data engineers. It accepts a PDF and an operation; outputs structured data suitable for indexing, reporting, or automation pipelines. The tool supports text extraction, metadata retrieval, page counting, and lightweight format conversions to text or HTML. It can apply optional page ranges and language hints to focus results. Outputs include extracted_text, metadata fields, page_count, word_count, and a downloadable result in the chosen format. The underlying logic uses standard PDF parsing rules, with an OCR fallback for image-based PDFs to maximize content recovery. It is designed for integration into data pipelines, archival workflows, and compliance reporting. Unique value lies in producing a consistent, machine-readable schema across operations, enabling easy ingestion into search indexes, data lakes, or BI tools. Use cases include indexing research papers, compiling metadata for regulations, and preparing extracts for QA checks or translations. Core features emphasize deterministic outputs, support for batch processing, and export options that reduce downstream manual processing.