Active build · Azure AI · RAG · MLOps
Bilingual Azure AI Customer Service Platform
A production-oriented reference implementation for English, Arabic and mixed-language customer service, with grounded retrieval, planned escalation-risk ML and release controls around evaluation, monitoring and rollback.
The problem
What this project is solving
A bilingual customer-service platform needs more than fluent answers. It has to retrieve the right source across English, Arabic and mixed-language queries, evaluate each language independently, and make changes traceable across prompts, indexes, embeddings, models and releases.
Implementation
What I built
- Created the first Azure AI Search bilingual retrieval baseline from five synthetic retail customer-service documents.
- Processed the documents into 22 indexed chunks using multilingual embeddings.
- Tested English, Arabic and mixed-language retrieval and tuned the mixed-language ranking behaviour.
- Designed the next stages for grounded generation, Azure ML escalation-risk scoring, release gates, monitoring and rollback.
Only the retrieval baseline described above is presented as completed. Generation, Azure ML, CI/CD and full monitoring are planned stages.
Evidence
Reference results
Delivery perspective
Why this matters
The operating challenge is the useful part: knowing when the system gets worse, which component changed, whether Arabic quality regressed and how to recover safely. That is the difference between an AI demo and an AI service that can be supported.