English

The PDF extractor online tool analyzes PDF documents to retrieve content such as native text, tables, and embedded metadata. It supports both electronically produced PDFs and scanned documents via OCR and provides outputs in TXT, JSON, CSV, and XML for downstream workflows.
Conceptually, the tool performs layout-aware extraction: it identifies blocks of text, table grids, and metadata fields by examining fonts, spacing, and table rules. For scanned pages, OCR converts images to text and can use language models to improve accuracy. Users can select which components to extract and adjust the depth of table recognition.
Intended users include researchers collecting data from academic papers, students digitizing notes, legal or compliance teams extracting clauses, and data scientists integrating PDFs into data pipelines. The tool emphasizes reliability, batch processing, and compatibility with common data formats to streamline indexing, search, content repurposing, and archival tasks.
Unique value lies in combining layout-aware extraction with flexible output options and OCR-enabled handling of low-quality scans, all without editing the source document. Core features include selective extraction targets (text, tables, metadata), optional OCR language support, batch processing, and export as TXT, JSON, CSV, or XML. Use cases range from converting research papers to structured datasets to building searchable archives.