Back

Case Study

UNRWA Digital Archive

An Azure-based digital archive designed to ingest, classify, store, and retrieve 16 million documents across five countries.

Role

Senior Software Engineer Consultant

Period

Apr 2026 – Present

Location

Remote · Luxembourg

Stack

Next.js, Node.js, Azure Functions

The Challenge

Create a controlled, country-by-country path for digitizing a very large archive while keeping document processing scalable, searchable, and reviewable by people.

Engineering Approach

We separated ingestion into event-driven stages using queues, serverless functions, blob storage, and structured metadata. Automated extraction feeds a Next.js review workflow so uncertain records can be corrected without blocking the wider pipeline.

What I Worked On

• Co-designed the event-driven archive architecture and country-by-country rollout
• Built ingestion workflows with Node.js, Azure Functions, queues, blob storage, and Azure SQL
• Integrated Azure Document Intelligence and AI Search for classification and retrieval
• Built a Next.js human-review interface for validating extracted data
• Delivered an internal documentation portal for stakeholders and engineers

Tech Stack

Next.jsNode.jsAzure FunctionsAzure SQLBlob StorageQueue StorageAI SearchDocument Intelligence

Impact

→ 16M-document architecture
→ 4M documents ingested
→ 86%+ extraction accuracy
→ Five-country rollout

Related Expertise

AI systems ↗Azure document AI ↗

Want something similar?Let’s talk →