The Product

How Parseloom extracts your document data

From upload to structured output: field detection, template mapping, and ERP-ready export in one pipeline.

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Abstract visualization of document field extraction and data structuring

Extraction Pipeline

From PDF to structured data in four steps

1

Document ingested

REST upload, S3 bucket, or email ingest. Native PDF, scanned TIFF, or image formats accepted.

2

Field detection pass

AI locates field zones in the document - identifying where vendor names, amounts, dates, and line items sit.

3

Template match

Detected zones map to your field schema. New document templates are learned from 5-10 labeled examples.

4

Structured export

JSON webhook, CSV, or direct ERP connector. Data arrives in your system within seconds of upload.

Field Support

Every field type your back-office team needs

Parseloom handles the full range of fields found in AP, logistics, and operations documents.

Dates and date ranges
Amounts, subtotals, and tax calculations
Line item tables (multi-row)
Party names (vendor, shipper, consignee)
Reference numbers (invoice, PO, BOL, PRO)
Addresses and postal codes
Date fields
invoice_date 2024-11-14
due_date 2024-12-14
Amount fields
subtotal 505.50
total 556.05
Reference fields
invoice_number INV-0891
po_number PO-44822
Party fields
vendor Pacific Supply
billing_address Austin TX

Developer Access

REST API that fits your integration stack

POST a document, get structured JSON back. Webhook push when extraction completes. No polling required.

API key or Bearer token auth
Webhook push on extraction complete
Field schema as JSON definition

Accuracy

What 94% field accuracy means in practice

Measured on our internal beta dataset of 500+ template types. Here's what we count as a correct extraction, and where our numbers hold up versus where they don't.

Dates and reference numbers
97%+
High pattern consistency across vendors. Date formats normalized automatically.
Currency amounts and totals
95%
Including calculated totals with tax. Failures typically involve multi-currency edge cases.
Line item tables
91%
Multi-row tables with varied column layouts. Lowest for scanned documents with low print quality.
Party names and addresses
93%
Highest accuracy on printed documents. Handwritten vendor stamps lower this on some invoice types.

See it work on your documents

Free tier, no credit card. Upload your first document and get structured JSON back in under 10 minutes.

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