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Document Processing

CTO

Production

How to maintain industry-leading product performance with the same staff as workloads and complexity increase dramatically, without compromising personal data security.

Context

A growing remote-identity-verification scale-up is expanding into both new geographies and new industries. This impacts significantly the complexity and the amount of workload for the machine learning and the data science teams.

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Each country has a variety of document types (passport, driver's license, ID card, utility bill, professional license, etc.) and each document type has a number of versions that can be supported. The set of required documents changes according to use cases (financial services, mobility, healthcare, gaming, etc.) and new documents are issued regularly.

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4 types of Computer Vision analysis are performed on each document: Detection, Segmentation, Classification and Tampering.

why choose us

4 weeks

From 3 months to 4 weeks to deploy a new tampering model in production.

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2 weeks

From 4 months to 2 weeks to support a new document in production.

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Double

The number of countries and user-cases addressed.

Challenge

Manage increasing workloads and complexity with the same number of people.

Continually add new document types and versions to the datasets.

Keep up with customer demands and fraudsters by training and deploying updated models.

Maintain ownership of personal data and ensure its security.

Solution

Tagging System: Organize data efficiently by tagging documents by type, country, format, security features, etc.

Dataset versioning: Enrich datasets with new documents and human-reviewed production images. Track dataset evolution.

Continuous training & deployment: Automatize model improvement and deployment.

Hybrid deployment: Store data and deploy models on their own infrastructure. Leverage the Picsellia GDPR infrastructure for model training.

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