Zero setup, zero training
No templates, no labeled data, no schema files. Drop the document in and Docusift returns clean structured data.
1099 Forms extraction
Extract Boxes and amounts from 1099 Forms
Pull every boxes and amounts value out of any 1099 forms — including scans and multi-page variants — into clean structured JSON. Each value carries a confidence score and a citation back to its source pixel.
Pulling boxes and amounts out of a 1099 form by hand is slow, and it is exactly where a mistake slips through. A 1099 comes in several variants — NEC, MISC, INT, DIV, K — each with its own numbered boxes, and tax software needs every box mapped to the right code for the right variant. A nonemployee-compensation figure typed into the wrong box is a filing error.
Docusift detects the 1099 variant, maps every numbered box to its code, and pulls the payer, recipient, and masked TIN blocks into structured fields, so the amounts drop into tax prep without hand-checking each box against the form.
Each extracted value ships with a per-field confidence score and a citation back to the exact spot on the page it was read from, so low-confidence boxes and amounts route to review automatically — and the clean data pushes to Google Sheets, a webhook, QuickBooks, or Xero.
| Box | Label | Amount |
|---|---|---|
| 1 | Nonemployee compensation | 24,500.00 |
| 4 | Federal income tax withheld | 0.00 |
| 5 | State tax withheld | 0.00 |
| 6 | State / Payer state no. | OH / 4471 |
Example structured output
{
"document_type": "form_1099",
"variant": "1099-NEC",
"tax_year": 2025,
"payer": { "name": "Northwind Manufacturing", "tin_masked": "**-***4471" },
"recipient": { "name": "Ironline Fabrication LLC", "tin_masked": "**-***0219" },
"box1_nonemployee_compensation": 24500.00,
"box4_federal_withholding": 0.00,
"confidence": 0.99
}Why teams choose Docusift
A confidence score on every field
Every value ships with a confidence score and a citation back to the source pixel in the original document, so low-confidence fields route to review instead of landing unchecked.
Fast turnaround
Seconds per document, not minutes. Built for production pipelines, not batch jobs.
Privacy first
Workspace-isolated processing, encrypted in transit and at rest, and one-click data deletion.
Frequently asked questions
How do I extract boxes and amounts from 1099 forms?
Upload the 1099 forms to Docusift via the dashboard, the REST API, or by emailing it to your workspace inbox. Docusift returns structured JSON with every boxes and amounts value, its confidence score, and a citation back to the source pixel — typically in under a second per page.
What is the best way to pull boxes and amounts from 1099 forms automatically?
The best way is a tool that reads layouts visually rather than matching templates. Template tools break when a vendor changes their format; Docusift parses each 1099 form from scratch, so it works on multi-page, multi-currency, and scanned variants without per-vendor configuration.
Does it work on scanned 1099 forms?
Yes. OCR, layout analysis, and field extraction run in a single pass, so scans, mobile photos, and native PDFs use the same endpoint and reach the same accuracy bar.
Can I push the extracted boxes and amounts into my own system?
Yes. Receive structured JSON via REST, hit a webhook, or sync directly into Google Sheets, your data warehouse, or your accounting tool.
How accurate is Docusift at extracting boxes and amounts?
Docusift reads each 1099 form visually rather than matching a template, and every extracted value ships with a per-field confidence score and a citation back to the source pixel — so low-confidence boxes and amounts route to human review automatically instead of landing unchecked.
Do I need to train a model first?
No. Docusift recognizes hundreds of document types out of the box. Custom fields are configured with a single sentence — no labeled training data required.
How is pricing calculated?
Pay per page processed. There is a free tier for evaluation and volume discounts for production workloads. No seat fees.
Can Docusift handle scanned or photographed documents?
Yes. The pipeline runs OCR + layout analysis + extraction in one pass, so scans, mobile photos, and native PDFs all flow through the same endpoint.
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