Airparser
Summary
Copy-pasting invoice line items into a spreadsheet is the kind of work that eats an afternoon and breaks the moment a vendor changes their PDF layout. Airparser exists to replace that loop with a rules-based extraction engine you describe once and run against every document that follows.
Airparser takes unstructured documents — emails, PDFs, scanned forms, handwritten notes — and pulls structured fields out of them using GPT-based extraction rules the user defines. The workflow is: import a document, describe what fields you want, and the engine returns a clean JSON or CSV you can route into Google Sheets, a CRM, or a downstream automation. It holds up well for finance teams processing consistent invoice formats and HR teams ingesting CVs at volume. The ceiling appears when document layouts vary enough that a single extraction schema stops covering all variants — teams end up maintaining multiple schemas rather than one. Documents that require cross-referencing data across pages or multi-table reconciliation push outside what the extraction model reliably handles.
Bottom line: Pick Airparser for a finance or HR team drowning in a single well-defined document type; plan a custom extraction pipeline when your documents are structurally inconsistent enough that no static schema survives the full intake volume.
Pricing Plans
Subscription- Price
- $33–$249/month (annual billing); free trial with 30 credits
- Free Tier
- 30 non-renewable credits in trial; 1 credit = 1 PDF page / 1 email / 1 image / 1 HTML document
Trial
30 non-renewable credits, 30 days document retention, all features included
- 30 credits (parse emails, PDFs, documents)
- OCR support
- LLM Vision engine
- Test all features
Starter
100 credits per month, 30 days retention, billed annually (~17% discount vs monthly)
- 100 credits/month
- OCR support
- LLM Vision engine
- API, Webhooks & Integrations
Growth
500 credits per month, 90 days retention, billed annually
- 500 credits/month
- 90 days document retention
- OCR support
- LLM Vision engine
- API, Webhooks & Integrations
Business
2000 credits per month, 90 days retention, unlimited team members, most popular, billed annually
- 2000 credits/month
- 90 days document retention
- OCR support
- LLM Vision engine
- Unlimited team members
- API, Webhooks & Integrations
Premium
5000 credits per month, 180 days retention, unlimited team members, billed annually
- 5000 credits/month
- 180 days document retention
- OCR support
- LLM Vision engine
- Unlimited team members
- API, Webhooks & Integrations
View full pricing on airparser.com →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- Handles email, PDF, scanned images, and handwritten forms through a single extraction interface, so teams avoid maintaining separate parsing tools for each document type they receive.
- Extraction rules are defined in plain language rather than code, which means a finance or HR manager can build and adjust schemas without pulling in an engineer every time a field changes.
- API access lets engineering teams embed document intake into existing pipelines programmatically, so Airparser can sit invisibly inside a larger automation rather than requiring a separate manual step.
- Native integrations with tools like Google Sheets and CRM platforms route extracted data directly into downstream systems, cutting out the manual export-import cycle that turns document processing into a bottleneck.
- Processes handwritten notes and forms into structured output, which removes the manual transcription step that typically makes paper-based workflows incompatible with digital automation.
Cons
Sign in to edit- When a single document category — say, vendor invoices — arrives in structurally different layouts from different senders, one extraction schema stops covering all variants reliably. Teams end up building and maintaining a separate schema per layout, which erodes the time savings the tool was bought to create.
- Multi-table documents or data that spans page breaks return inconsistent extraction results. Finance teams processing complex purchase orders with line-item tables that overflow a single page report needing manual correction at a rate that makes automation marginal.
- There is no built-in validation layer: extracted data ships to the destination without being checked against external records or business rules. Teams that need extracted invoice amounts reconciled against a PO system before they post have to build that logic externally — at which point they are maintaining the integration themselves.
- Teams whose document workflows require branching logic after extraction — route to approver A if amount exceeds threshold, flag for review if vendor is new — find no native way to express that inside Airparser and move to a full document processing platform like Rossum or a workflow tool like Make to get it done in one system.
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About
- Platforms
- Web, API
- API Available
- Yes
- Self-Hosted
- No
- Last Updated
- 2026-06-03T08:52:23.261Z
Best For
Who it's for
- Businesses processing high volumes of diverse document types
- Finance and accounting teams automating data entry from invoices
- HR departments handling resume and employment verification data
- Operations teams digitizing unstructured documents and forms
- Companies building automation workflows across tools like Google Sheets and CRM platforms
What it does well
- Extracting structured data from emails and lead capture
- Automating invoice, receipt, and purchase order processing
- CV and resume parsing for recruitment workflows
- Contract and agreement data extraction and management
- Digitizing handwritten notes and forms into structured data
Integrations
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Frequently Asked Questions
- Is Airparser free?
- Airparser is a paid tool ($33–$249/month (annual billing); free trial with 30 credits). No permanent free tier is offered.
- Is Airparser open source?
- No — Airparser is a closed-source tool. Source code is not publicly available.
- Does Airparser have an API?
- Yes. Airparser exposes a developer API. See the official documentation at https://airparser.com for details.
- When was Airparser released?
- Airparser was first released in 2023.
- What platforms does Airparser support?
- Airparser is available on: Web, API.
Hours Saved & ROI Stories Community
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Airparser accepts documents through email forwarding, direct upload, or API and applies GPT-powered extraction rules to pull named fields into structured output. The core workflow is declarative: you tell the tool what fields to extract, it learns the pattern from examples, and every subsequent document of that type gets processed against the same schema. Output lands in JSON, CSV, or directly in connected tools via webhooks and integrations. No code is required to set up basic extraction — which is the point for operations teams who are not running an engineering function.
The differentiating feature is the breadth of document types it handles without format-specific preprocessing. Invoices, purchase orders, CVs, contracts, handwritten forms, and email bodies all pass through the same extraction interface rather than requiring separate tools or parsers per file type. For teams receiving documents in mixed formats from external sources they do not control, this matters — the alternative is either a purpose-built parser per document category or significant manual triage upstream.
Airparser fits cleanly inside mid-volume document intake workflows where the document structure is reasonably consistent and the goal is eliminating data entry rather than building a decision engine. It breaks down when documents contain tables that span multiple pages, when extracted fields need to be validated against external data sources before they land, or when business logic beyond extraction — approval routing, anomaly flagging — needs to be embedded in the same pipeline. Teams that need those capabilities typically add a workflow automation layer on top, or migrate to a document processing platform that bundles extraction with process logic. The API is available for teams that want to push documents programmatically rather than through the web interface.