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AI & Data Published: 02 Nov 2025 Reading time: 5 min read

Building AI Observability for Mission-Critical Apps

Telemetry recipes for tracking drift, bias, and latency in national-scale AI services.

Author: Hassan Al-Mansour · Head of Intelligent Platforms
Streaming dashboards surface anomalies in under 60 seconds.
Bilingual evaluation sets catch linguistic bias early.
Automated rollback plans guard against costly downtime.

Instrument every model touchpoint

We capture prompts, feature vectors, inference metadata, and downstream actions to understand exactly how models behave in production.

Human-in-the-loop review cycles

Operations teams receive curated cases each week, mixing Arabic and English data, to score relevance, fairness, and impact.

Close the feedback loop

Insights travel back into retraining sprints, feature flags, and rollback plans so nothing stays theoretical.

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Community discussion

Leaders from government, finance, and energy comment on our weekly drops.

Reem Al-Salem

AI Program Manager

04 Nov 2025

Love the mention of bilingual eval sets—rarely discussed publicly.

Faisal Al-Dosari

Data Platform Lead

07 Nov 2025

How do you version prompts? Would like a follow-up article.

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