Airparser is a GPT-powered document parser that extracts structured data from emails, PDFs, and any text document.
Airparser turns unstructured documents into clean, structured data. Forward emails or upload PDFs, and it extracts the fields you define — names, amounts, dates, line items — using large language models that understand context rather than fixed templates. Extracted data exports to Google Sheets, webhooks, and thousands of apps through Zapier and Make. It handles documents that traditional OCR-based parsers fail on, like varied invoice layouts and messy email bodies.
Where template parsers break on layout drift, Airparser’s language-model core adapts: it understands that ‘Invoice #’ and ‘Document Number’ mean the same field. A review queue surfaces low-confidence extractions for human confirmation, keeping data quality high as volume grows.
The integration story makes Airparser practical: parsed records flow into spreadsheets, databases, and thousands of apps automatically. Operations teams commonly pair it with automation platforms to run intake workflows end to end without engineering support.
Airparser offers a free trial with document credits. Paid plans scale by monthly document volume and retention.
Operations teams automating intake of invoices, orders, applications, and any recurring document workflow.
A free trial covers evaluation; ongoing use is a paid subscription by volume.
Yes, Airparser provides a REST API and webhooks for embedding parsing into automated workflows.
Template-based parsers like Klippa excel on standard formats; Airparser’s LLM core handles the long tail of document variation.
Yes, forwarding emails to your Airparser inbox automatically extracts data from the body and attachments.
Exports reach Google Sheets, webhooks, and thousands of apps through Zapier and Make integrations.
LLM-assisted extraction handles many handwriting cases, with quality depending on legibility.
Nested schemas capture line items and repeated structures, not just flat key-value fields.
Yes, structured field extraction works on contracts as well as transactional documents.
Documents typically parse within seconds, and extracted records reach your connected tools through webhooks immediately after processing.