Document to CSV

The tool accepts several document formats that contain tables and returns a CSV representation suitable for data pipelines. It detects tabular regions in JSON, XML, Excel, TSV, and PDF inputs, aligns columns, and applies consistent quoting rules to preserve data fidelity. The core workflow is format-agnostic in terms of data extraction, with format-specific parsers handling input parsing before table normalization. It supports header inference or a user-provided header, and allows configuring the output delimiter and encoding to match downstream systems. In multi-table documents, users can choose to merge tables into a single CSV or emit separate outputs per table, enabling flexible integration with data lakes and ETL jobs. The tool emphasizes correctness for numeric and date-like values, escaping and quoting where necessary, and robust handling of missing values. It is designed for automation, batch processing, and scripting where CSV is the lingua franca of data interchange. Unique value propositions include multi-format compatibility, configurable encoding and delimiter, and optional OCR support for scanned PDFs, which expands applicability to real-world document suites. Use cases include migrating data from annual reports (PDF tables), extracting form-like data from XML/JSON exports, and converting Excel workbooks with multiple sheets into CSV-ready datasets. Core features also cover error reporting and edge-case handling for encrypted or non-tabular inputs, enabling reliable integration into CI/CD pipelines and data workflows.