Case Study
Expatrio×Nanonets

From manual passport checks
to autonomous OCR extraction

Expatrio manually verified international passports for relocation customers — requiring multiple staff per document and breaking on low-quality images. A Nanonets OCR agent now classifies documents, extracts key fields, validates MRZ checksums, and flags fraud automatically.

95% Less Manual Entry94% Field Accuracy2-Day DeploymentGDPR Compliant
About the customerExpatrio

Expatrio Global Services GmbH is a Berlin-based fintech and relocation platform helping international students and professionals move to Germany. Their app guides customers through visa, banking, and health insurance requirements — with identity verification at the core of onboarding.

~50
Employees
2016
Founded
Germany
HQ
190+
Countries served

The Problem

Expatrio customers submit passport images as part of their relocation onboarding. Each document required multiple staff members to manually open, read, and enter passport fields into the internal system — a slow, expensive, and unscalable process.

  • Multiple employees needed per verification — no automation in the loop.
  • 190+ passport formats from different countries caused inconsistent extraction.
  • Low-quality images broke internal OCR tools with no graceful fallback.
Customer
Uploads passport
Email
Staff opens email
Manual
Data entry per field
Manual
Cross-check fields
Manual
Verify MRZ
CRM
CRM update
Manual process repeated per customer
5 min
Per document, manually
190+
Passport formats in scope
Stack
Web Upload API
Internal CRM

A great product and amazing customer support. Their response time was amazing. They went an extra mile.

Tay Kim
Product Operations Manager, Expatrio
Expatrio

The solution

One extraction agent. Every passport format, every field.

Nanonets replaced the manual passport review loop with one autonomous agent. The agent classifies each document, selects the right extraction template, pulls all key fields, validates the MRZ checksum, and flags any fraudulent or expired documents — with no human in the loop for clean passports.

Receive Document
Classify Passport
Extract Fields
Validate MRZ
Export Data

Pipeline overview

Upload API
Customer uploads passport
Web or mobile upload
Nanonets
Classify document
Passport vs ID vs Visa
Nanonets
Extract fields
Surname · Names · DOB · Nationality
Nanonets
MRZ validation
Checksum verified
CRM / App
Verified data
Exported to customer CRM
Nanonets
Flag issue
Expired or field mismatch
Manual review
Human verification
95% less manual entry · 94% field accuracy · International formats supported

Impact

95%
reduction in manual entry
5 min → 30 sec per document
94%
field accuracy
Top 4 fields extracted
2 days
to deploy
From setup to production
9/10
satisfaction score
Rated by Expatrio
Metric
Before
After
Improvement
Data entry time
5 min/document
30 sec
95% faster
Field accuracy
~80% (manual)
94%
14 pt improvement
Formats supported
Limited
190+ countries
Global coverage
Fraud detection
Manual spot-check
Automated MRZ validation
Every document
Deployment time
Months (internal)
2 days
Instant value

AGENT ANATOMY

Nanonets Agent
Autonomous action-taking
After extraction
Agent decides path and acts
Verified
All fields extracted
Upload API
Passport uploaded
Image quality OK ✓
Queued for classify ✓
Document ID assigned ✓
Nanonets
Classified
Type: Passport ✓
Country: Germany ✓
Template loaded ✓
Nanonets
Fields extracted
SurnameMÜLLER
Given NamesHANS PETER
NationalityDEU
Nanonets
MRZ validated
Checksum valid ✓
No anomalies ✓
CRM / App
Export to CRM
Fields4 verified
StatusSent ✓
Flagged
MRZ mismatch
Nanonets
MRZ checksum fails
⚠ Checksum mismatch
Nanonets
Flag document
StatusFlagged
Nanonets
listening…
Human
Human review queue
Awaiting review
Nanonets
Re-verified
StatusVerified ✓
Loops to Export
Low quality
Unreadable image
Nanonets
Quality check fails
Resolution too low ✗
Upload API
Rejected
StatusRejected ✗
Nanonets
listening…
Customer
Re-upload prompt
User re-uploads image
Nanonets
Quality check passes
StatusAccepted ✓
Loops to Extract

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