Pdf Parse
Parse PDFs into structured datasets. Define visual schemas, extract data into relational SQLite tables, or export to JSON and CSV for your data pipelines.
Turn PDFs into Structured, Queryable Databases
PdfParse transforms PDF documents into structured, queryable datasets. Instead of working with flat, unstructured files, you can design relational database schemas using an intuitive visual schema builder. Create tables, define columns, and attach AI prompts to each field to guide the extraction process.
You can build complex schemas with child tables for use cases like line items or transactions, complete with proper foreign-key relationships.
The primary output is a fully normalized SQLite database, which is far more efficient for AI agents and data analysis. LLM agents can query the database directly using SQL, consuming a fraction of the tokens compared to parsing large JSON files.
Key Features
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Visual Schema Builder
Design tables and fields visually, with AI prompts for precise data extraction. -
Relational Data Output
Generate normalized SQLite databases with foreign keys and clean structure. -
LLM Agent Ready
Run token-efficient SQL queries directly on the database. -
Flexible Exports
Download as SQLite or export individual tables to CSV, JSON, or XML.
Ideal for teams building AI workflows, analytics pipelines, or structured data systems from PDF-based sources.
