Google Cloud

Document AI Complete Guide: PDF/Image OCR, Invoices, Contracts & Custom Extractors

2026-05-24
NicheeLab Editorial Team

Document AI is GCP's document AI platform that automatically extracts structured data from PDFs and images. It ships with 50+ specialized processors (invoices, receipts, contracts, IDs, and more) on top of general-purpose OCR and Form Parser. Pair it with Gemini and you get a full document processing pipeline: OCR → structured extraction → summarization, classification, and Q&A.

Processor Types

CategoryProcessorUse Case
GeneralDocument OCRText extraction
GeneralForm ParserKey-value extraction
GeneralLayout ParserLayout structure extraction
FinanceInvoice ParserInvoices
FinanceExpense (receipts)Receipts
FinanceBank StatementBank statements
FinancePay Stub / W-2 / 1099Pay stubs and tax forms
IDUS Driver License / PassportID documents
Real EstateMortgage / LeaseMortgage and lease contracts
HealthcareHealthcare FormsMedical forms
CustomCustom Extractor / ClassifierIndustry-specific

Typical Pipeline

  1. Upload the document to GCS
  2. Eventarc trigger fires Cloud Run
  3. Extract with Document AI (e.g., Invoice Parser)
  4. Evaluate against a confidence score threshold (e.g., 0.85)
  5. Pass → auto-insert into BigQuery / your DB
  6. Fail → route to a Human-in-the-loop (HITL) review UI
  7. Layer on Gemini for summarization, classification, and Q&A

Python Sample (Invoice Parser)

from google.cloud import documentai_v1 as documentai

client = documentai.DocumentProcessorServiceClient()
processor_name = "projects/PROJECT/locations/us/processors/INVOICE_PROCESSOR_ID"

with open("invoice.pdf", "rb") as f:
    raw_doc = documentai.RawDocument(content=f.read(), mime_type="application/pdf")

request = documentai.ProcessRequest(name=processor_name, raw_document=raw_doc)
result = client.process_document(request=request)

for entity in result.document.entities:
    print(f"{entity.type_}: {entity.mention_text} (conf: {entity.confidence:.2f})")
# Example output:
# invoice_id: INV-2026-001 (conf: 0.99)
# total_amount: 12500 (conf: 0.98)
# supplier_name: ACME Corp (conf: 0.95)

Pricing (US, 2026)

ProcessorPrice / 1,000 pages
Document OCR$1.50
Form Parser$30
Layout Parser$10
Invoice / Expense / W-2$30
Mortgage / Loan$65
Custom Extractor (inference)$30
Custom training$5/h

Gemini Integration Pattern

# Structured extraction with Document AI
extracted = process_with_doc_ai(pdf_path)
text = extracted.document.text

# Summarize and answer questions with Gemini
from vertexai.generative_models import GenerativeModel
gemini = GenerativeModel("gemini-2.0-pro-001")

summary = gemini.generate_content(
    f"Summarize the following contract in 5 lines:\\n{text}"
)

answer = gemini.generate_content(
    f"Read the following contract and tell me the termination terms:\\n{text}"
)

Comparison with Other Cloud OCR Services

FeatureDocument AIAWS TextractAzure Form Recognizer
OCRExcellentExcellentExcellent
Form extractionExcellent (Form Parser)ExcellentExcellent
Specialized processors50+Invoices, receipts, IDsInvoices, receipts, IDs
Custom trainingExcellentExcellent (Custom Queries)Excellent (Custom Model)
OCR pricing$1.50/1k$1.50/1k$1/1k

Typical Use Cases

  • Accounting: automated ingestion of invoices and receipts (expense management SaaS)
  • Finance: verifying loan applications and pay stubs
  • Real estate: digitizing rental contracts
  • Healthcare: structuring insurance forms and medical reports
  • HR: parsing resumes and employment contracts
  • Logistics: shipping slips and customs documents

What is Document AI?

A managed service that automatically extracts structured data from PDFs and images. It combines OCR and ML to process invoices, receipts, contracts, forms, ID documents, and more.

What processors are available?

Document OCR (general purpose), Form Parser, Layout Parser, 50+ specialized processors (invoices, receipts, W-2, W-9, driver's licenses, passports, etc.), and Custom Extractor (trained on your own data).

What is the Custom Extractor?

A feature for handling industry-specific forms by labeling and training the model yourself. Combine it with the Custom Document Classifier to build a fully bespoke document processing pipeline.

How is pricing structured?

Document OCR is $1.50 per 1,000 pages, Form Parser is $30 per 1,000 pages, and specialized processors run $30-65 per 1,000 pages. Custom processors charge separately for training and inference.

How does it integrate with Vertex AI and Gemini?

The standard pattern is extract with Document AI, then summarize, classify, or answer questions with Gemini. You can also feed the output into Vertex AI Search to power a RAG-based architecture.

Is Document AI Warehouse deprecated?

Yes — it was deprecated in 2024 and folded into Vertex AI Search. Long-term storage plus search is now handled through Vertex AI Search by default.

How does it compare to other cloud OCR services?

AWS Textract and Azure Form Recognizer offer comparable capabilities. Document AI's strength is the broadest catalog of specialized processors, with strong HIPAA and PCI compliance coverage.

How do you use confidence scores?

Every extracted value comes with a confidence score from 0 to 1. The standard pattern is to route anything below your threshold to a Human-in-the-loop (HITL) review queue.

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* Google Cloud is a trademark of Google LLC. For the latest information, see the official Document AI documentation.

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NicheeLab Editorial Team

NicheeLab editorial team focused on data engineering and cloud certification learning. Content is structured around practical study needs and official exam domains.


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