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ParseFlow

AI-Powered PDF Data Extraction for macOS

AILaunched Jul 2026

The story

ParseFlow is a privacy-first PDF data extraction tool for macOS, powered by open-source AI models running locally on Apple Silicon. It enables users to extract structured data from any PDF document, including invoices, receipts, contracts, and reports, without any cloud processing or subscriptions. With a one-time purchase, users can batch process up to 100 PDFs at a time, define reusable extraction templates, and export results in CSV, JSON, or Excel formats—all while ensuring that no data ever leaves their Mac.

Overview

ParseFlow is designed for professionals and organizations that need to extract structured data from PDF documents while maintaining strict privacy and data security. Unlike cloud-based alternatives, ParseFlow operates entirely on-device, leveraging open-source AI models (Gemma 3 by Google) accelerated by Apple Metal GPU. This ensures that sensitive documents never leave the user's Mac, making it ideal for industries with stringent privacy requirements such as accounting, legal, healthcare, and finance.

The workflow is straightforward: users define a data extraction schema using a visual editor, drag and drop up to 100 PDFs at once, and review the extracted data side-by-side with the original document. The AI model processes both native and scanned PDFs, supporting OCR via Apple's Vision framework, and allows for easy editing and export of results. ParseFlow also features a chat interface for querying PDFs in natural language, all processed locally.

With a one-time purchase model, ParseFlow eliminates recurring fees and usage limits, offering unlimited processing and all future updates. The product is GDPR-friendly by design and includes transparency features such as a Privacy & Network panel to verify zero data transmission. This makes ParseFlow particularly suitable for users who value privacy, cost-effectiveness, and full control over their document workflows.

Key features

Local AI-Powered Extraction

Extracts data from PDFs using open-source AI models running entirely on your Mac, ensuring privacy and speed.

Batch Processing

Process up to 100 PDFs at once with reusable extraction templates for efficient workflows.

Flexible Schema Editor

Create and reuse custom data extraction templates for various document types using a visual editor.

Side-by-Side Review and Editing

Review extracted data alongside the original PDF, edit fields, and view confidence scores before exporting.

Offline and Private

Works completely offline after initial model download, with no cloud processing or data transmission.

Multi-Format Export

Export extracted data to CSV, JSON, or Excel formats with a single click.

Use cases

  • 1

    Accounting and Finance

    Automate extraction of invoice numbers, totals, and line items from financial documents for bookkeeping and analysis.

  • 2

    Legal Document Processing

    Extract key data from contracts, agreements, and legal forms while maintaining client confidentiality.

  • 3

    Healthcare Administration

    Securely process patient forms, medical reports, and insurance documents without risking data privacy.

  • 4

    Government and Compliance

    Handle sensitive government documents and compliance paperwork entirely offline to meet regulatory requirements.

FAQ

Is my data really private?

Yes, ParseFlow processes all documents locally on your Mac with no data uploaded to any server, ensuring complete privacy.

Do I need an internet connection to use ParseFlow?

Internet is only required for the initial AI model download; after that, ParseFlow works fully offline.

What AI model does ParseFlow use?

ParseFlow uses Gemma 3 by Google, an open multimodal model running locally via llama.cpp with Metal GPU acceleration.

Can I use ParseFlow on multiple Macs?

Yes, you can install and use ParseFlow on any of your personal Macs with a single purchase.

What types of PDFs are supported?

ParseFlow supports native text PDFs, scanned PDFs (with OCR), fillable forms, and both single-page and multi-page documents.

Tech stack & tags

#tauri#pdfkit#vision#llama.cpp#metal#gemma 3#pdf#macos#offline#ai#data extraction#privacy#batch processing#local

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