Azure AI Document Intelligence
- Azure AI Document Intelligence: extraction specialist. The result is a dataset — you build archive, review and workflow around it.
vs Azure AI Document Intelligence
Azure DI vs. finished document path: 69 types, boxes and archive in the EU.
Made for real business. Not for hype.
API output from July 14, 2026
Source document (invoice) · from €9 per 1,000 pages
Extracted fields · from €9 per 1,000 pages
| # | SKU | Description | Unit | Qty | Rate | Amount |
|---|---|---|---|---|---|---|
| 1 | ITEM-92912 | Multifold paper towels (case, 16 packs) | case | 40 | $42.11 | $1,684.40 |
| 2 | PN-61493 | Foaming hand soap refill, 1200 mL (case of 4) | case | 4 | $38.81 | $155.24 |
| 3 | PART-33106 | 55-gallon trash can liners (case of 100) | case | 9 | $53.07 | $477.63 |
LLM fields — natural language
Accounts payable
Prompt
Based on the total amount, check whether this invoice exceeds the dual-control limit of USD 2,000 and therefore needs a second approval.
Result
Yes — USD 2,527.98 exceeds USD 2,000. Second approval required.
Document INV-59762 · field _total_amount
KYC / HR / legal capacity
Prompt
Based on the date of birth on the ID document, check whether the person is of legal age (18) as of today.
Result
Yes — date of birth 12 Mar 2004 → of legal age on the reference date (22 years).
ID / passport pipeline · LLM field instead of a fixed template key
Compliance / vendor screening
Prompt
Based on supplier name and address, check whether the issuer is located in the USA and must be treated as a third-country vendor for EU booking.
Result
Yes — Pristine Galvan Inc., Cleveland OH (USA). Third country / US vendor.
Document INV-59762 · address + company name via LLM prompt
Agent UI: extracted data (raw JSON)
JSON excerpt (7 fields + 3 line items)
{
"_supplier_name": {
"value": "Pristine Galvan Inc.",
"value_raw": "Pristine Galvan Inc."
},
"_invoice_number": {
"value": "INV-59762",
"value_raw": "INV-59762"
},
"_invoice_date": {
"value": "07/07/2026",
"value_raw": "2026-07-07"
},
"_currency": {
"value": "USD",
"value_raw": "USD"
},
"_net_amount": {
"value": "$2,317.27",
"value_raw": "2317.27"
},
"_vat_amount": {
"value": "$162.21",
"value_raw": "162.21"
},
"_total_amount": {
"value": "$2,527.98",
"value_raw": "2527.98"
},
"_line_items": [
{
"sku": "ITEM-92912",
"description": "Multifold paper towels (case, 16 packs)",
"qty": 40,
"unit": "case",
"rate": "$42.11",
"amount": "$1,684.40",
"amount_raw": "1684.40"
},
{
"sku": "PN-61493",
"description": "Foaming hand soap refill, 1200 mL (case of 4)",
"qty": 4,
"unit": "case",
"rate": "$38.81",
"amount": "$155.24",
"amount_raw": "155.24"
},
{
"sku": "PART-33106",
"description": "55-gallon trash can liners (case of 100)",
"qty": 9,
"unit": "case",
"rate": "$53.07",
"amount": "$477.63",
"amount_raw": "477.63"
}
]
} In the same account
AI OCR with bounding boxes — 69 types, fields with location.
from €9 per 1,000 pages
Seamless in the job path — task and document also on mobile.
Web + Mobile
SES signatures from the same credit balance.
SES from the balance
Audit-proof filing and audit trail.
included
Details for Azure AI Document Intelligence from an official source, retrieved 08/2026.
| Criterion | PaperOffice | Azure AI Document Intelligence |
|---|---|---|
| Bounding boxes (word/line level) | Yes (word/line level, Surya OCR) | Yes (layout/prebuilt geometry) |
| Sandwich PDF / searchable archive PDF | Yes — searchable archive PDF | no — no native DMS sandwich |
| Click-to-evidence / visual validation (HITL) | Yes — click-to-evidence / HITL | no PaperOffice HITL on the object |
| Structured IDP fields (ready types) | 69 ready document types incl. DATEV/ZUGFeRD/XRechnung | Read/Layout/Prebuilt/Custom (formerly Form Recognizer) |
| DMS/archive included (WORM, audit, legal hold) | Yes — WORM, audit trail, legal hold | no — plan separately |
| E-signatures on the same document | Yes — on the same document in the archive | no |
| Native MCP server (tool count) | Yes — 300+ API/MCP Tools | no — Azure ecosystem |
| EU inference on owned hardware | Yes — owned EU GPU hardware | Azure regions — Microsoft cloud |
| Self-service without cloud setup | Yes — token in minutes | Azure subscription + resources |
| Pricing model | One credit balance for all features: from €9.00–€30.00 per 1,000 pages by quality tier | Read (reines OCR): $1.50 pro 1.000 Seiten |
| Billing | from €9.00 per 1,000 pages (Elite) — same scale on every tier | n/a |
Source: https://learn.microsoft.com/en-us/answers/questions/5927427/azure-document-intelligence-pricing, retrieved 08/2026.
Our prices are public — including partner terms.
Unit: Price per 1,000 pages
| Tier | Elite Partner (−70%) | Partner (−40%) | Enduser |
|---|---|---|---|
| Basic | €9.00 | €18.00 | €30.00 |
| Premium | €12.00 | €24.00 | €40.00 |
| Ultra | €30.00 | €60.00 | €100.00 |
Billing is internal in credits; amounts follow the selected currency (base: list price).
Elite terms after qualification — criteria and program are public: Pricing · Partner program
Teams already deep in Azure (IAM, storage, pipelines) that only need raw or prebuilt extraction often stay cheaper there — Read/prebuilt sit around $1.50–$10/1,000 pages per sources. The surrounding stack already exists.
When IDP, DMS/WORM and EU-owned inference are needed without separate cloud plumbing, PaperOffice is the better fit.
Trusted by leading companies worldwide
Read (reines OCR): $1.50 pro 1.000 Seiten. With PaperOffice result, archive and further processing live in one account with one credit balance.
Azure AI Document Intelligence typically returns a dataset — you build archive and residency around it. PaperOffice runs its own EU servers and files the result in an audit-proof way.
https://api.paperoffice.ai/latest/docs/llms-full.txt Or connect directly: MCP server for Claude, Cursor and ChatGPT →
Invoice extraction
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=invoice"
# danach job_result pollen (job_id aus Response) import requests
api_token = "po_sk_xxx"
file_path = "invoice.pdf"
create = 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": "invoice"},
)
print(create.json()) {
"status": "success",
"job_id": "job_…",
"result": { "fields": { "invoice_number": "…" } }
} Full parameters: llms-full.txt / Postman.
Yes. PaperOffice AI can be evaluated as an alternative to Azure AI Document Intelligence — along extraction, processing on own servers in the EU, DMS/WORM and MCP, API-first and without disparagement.
Basic 3¢, Premium 4¢, Ultra 10¢ per page — the full price list is public. What Azure AI Document Intelligence costs is in the comparison table above, with source and date.
Typical cutover from Azure AI Document Intelligence: send the same files to PaperOffice workflows (e.g. idp_collection=invoice), run in parallel, then cut over. llms-full.txt: job/workflow.
On our own servers in the EU — including audit-proof filing and an audit trail. Where Azure AI Document Intelligence processes data is documented by the vendor.
Yes as an evaluation target next to Azure AI Document Intelligence: Form Recognizer is the former Azure name; the comparison covers Azure Document Intelligence. Fastest with llms-full.txt.
Konfuzio: sales-led IDP — PaperOffice: self-service list price.
PaperOffice vs Konfuzio →Rossum compared: extraction and archive in one system — or separate worlds?
PaperOffice vs Rossum →ABBYY (Vantage / FlexiCapture) compared: extraction and archive in one system — or separate worlds?
PaperOffice vs ABBYY (Vantage / FlexiCapture) →Mistral OCR 4: strong paragraph boxes — PaperOffice: word/line boxes, sandwich PDF, IDP, DMS/WORM, HITL, MCP.
PaperOffice vs Mistral OCR 4 →Google Document AI: extraction with geometry — PaperOffice closes sandwich PDF, DMS/WORM and MCP.
PaperOffice vs Google Document AI →AWS Textract: extraction with geometry — PaperOffice adds sandwich PDF, DMS/WORM, HITL and MCP on the object.
PaperOffice vs AWS Textract →Get a token, review pricing, compare the feature matrix.