Extract · Payroll / pay stub
Extract Payroll / pay stub via API — structured data from 3¢/page
PaperOffice AI extracts Payroll / pay stub data via API using LLM-based semantic extraction combined with Surya OCR geometry. Pricing from 3¢/page (Basic); Premium and Ultra for higher model tiers. Payroll / Pay Stub Extract salary and payroll data. Fields: employee_name, pay_period, gross, net, deductions, taxes, employer
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Extracted fields
Source: Extract payroll / pay stub · POST https://api.paperoffice.ai/latest/job/add/workflow
| Field / description |
|---|
| employee_name |
| pay_period |
| gross |
| net |
| deductions |
| taxes |
| employer |
Code example
curl
curl -X POST "https://api.paperoffice.ai/latest/job/add/workflow" \
-H "Authorization: Bearer po_sk_xxx" \
-F "[email protected]" \
-F "model=premium" \
-F "idp_collection=payroll"Python
import requests
api_token = "po_sk_xxx"
file_path = "document.pdf"
response = requests.post(
"https://api.paperoffice.ai/latest/job/add/workflow",
headers={"Authorization": f"Bearer {api_token}"},
files={"file": open(file_path, "rb")},
data={"model": "premium", "idp_collection": "payroll"},
)
job_result = response.json()
print(job_result)Example response
{
"status": "success",
"job_id": "job_…",
"result": {
"idp_collection": "payroll",
"fields": {
"employee_name": "…",
"pay_period": "…",
"gross": "…",
"net": "…",
"deductions": "…"
}
}
}Truncated schema — full fields in llms-full.txt / Postman.
Pricing
| Tier | Price / page |
|---|---|
| Basic | 3 ct / €0.03 |
| Premium | 4 ct / €0.04 |
| Ultra | 10 ct / €0.10 |
API credit note: 10 credits (base, at `priority=500`)
FAQ
What does extracting Payroll / pay stub cost?
AI DMS / IDP processing costs Basic 3¢, Premium 4¢ and Ultra 10¢ per page.
Which endpoint is used?
Per API docs: POST https://api.paperoffice.ai/latest/job/add/workflow (pipeline/slug: workflow).
Is extraction available via MCP?
Yes. The same capabilities are reachable via the PaperOffice MCP server — see /mcp/.
Where is data processed?
On PaperOffice EU infrastructure on owned hardware.
