Airparser

Airparser is a production-oriented document data extraction tool that uses large language models (LLMs) to automatically convert unstructured content into structured data. It is suitable for teams that need to extract information from large volumes of documents in batches, and setup and integration can be completed without writing code.

Purpose

Airparser's core purpose is to automate document data extraction, replacing manual entry. It can extract structured data from emails, PDFs (native or scanned), Word documents, images, HTML, CSV, and handwritten text, and export the results in real time to users' existing workflows.

Main Capabilities

• Support for multiple document types: Supports emails and attachments, PDFs, Word, images, HTML, CSV, handwritten text, and more. The official claim is that "if it can be read, it can be parsed."
• Natural language configuration: Users only need to describe the fields to extract in natural language (such as name, date, amount, order number, etc.), with no templates or training datasets required.
• High-accuracy extraction: Combines Text LLM, Vision LLM, and AI OCR engines. The official claim is that compared with traditional rule-based extraction methods, the error rate is reduced by 90%, and it can understand field meanings rather than relying only on position, so it still works when document layouts change.
• Multilingual recognition: Supports printed text, scanned documents, and handwritten text in more than 60 languages.
• Human review: Low-confidence documents can be held back for the team to verify, correct, and approve before entering the integration process.
• Real-time export and integration: Parsing results can be exported in real time to Google Sheets, Excel, CSV, and JSON, and integrated with more than 7,000 apps through Webhook, REST API, Zapier, Make, n8n, and others.
• AI code assistant: Users can describe the desired changes in natural language and receive directly runnable Python code without manual coding.

How to Use

1. Import documents: This can be done by forwarding emails and attachments to the Airparser inbox, manually uploading files, or importing through the API and automation platforms (Zapier, Make, etc.).
2. Describe fields: Create a list of fields and explain in natural language the data to be extracted.
3. Automatic extraction: Airparser automatically processes all incoming emails, attachments, and files.
4. Export and integration: The parsed data can be exported in real time to Google Sheets, documents.pieces, Webhooks, API, Zapier, and over 7,000 apps.

Officially, most users can complete their first document parsing within 5 minutes.

Use cases

• Extract lead details, order information, signatures, contact details, dates, and more from emails and text.
• Extract names, contact details, work experience, and more from resumes.
• Extract amounts, dates, ordered items, and supplier information from invoices, receipts, and purchase orders.
• Extract clauses, parties involved, and key data from contracts.
• Digitize handwritten notes, checklists, and more.
• Extract order numbers, items, and delivery details from order confirmation documents.
• Automatically export parsed data to Google Sheets, CRM, QuickBooks, cloud storage, etc., or send team notifications.

Limits and data protection

• Data security: Documents and extracted data are encrypted at rest using AES-256 and in transit using TLS 1.2+; compliant with major data protection regulations such as GDPR.
• Not used for AI training: The official statement explicitly promises that user documents and extracted data will not be used to train or improve any AI or LLM models.
• Automatic deletion: Documents and parsed data can be configured to be automatically deleted after processing.
• Free plan: You can start for free with no credit card required, and the free plan allows you to parse documents and explore all core features; paid plans unlock higher capacity and advanced features. Specific pricing is not yet provided.
• Demo upload limits: The demo page only supports uploading 1-page documents in PDF, JPEG, PNG, BMP, EML, or DOCX format, up to 10MB; files are not stored and are processed only in memory and discarded after returning the demo results.