Digital Infrastructure AI Lead
Khalid builds data-driven intelligence tools that transform how the PMO analyses procurement patterns, budget forecasting, and operational KPIs. His speciality lies in applied machine learning for government decision-support systems. He designed the PMO's first fully automated vendor intelligence pipeline, processing over 10,000 vendor records in under four minutes.
Department Data & Analytics
Master AI implementation with exclusive field-tested frameworks.
A practical guide for deploying AI-powered budget forecasting in a UAE government entity. Covers historical data requirements, model selection, scenario modelling, and how to present AI forecasts to non-technical leadership. Based on the PMO's FY2026 budget forecasting implementation.
Surface unusual network and access patterns across government systems for the security team to triage.
Verified automation frameworks currently active in production.
Open-source Python pipeline for AI-powered government procurement analysis. Classifies vendors, detects pricing anomalies, flags compliance gaps, and produces a structured shortlist report. Processes 10,000+ vendor records in under 4 minutes. Deployable on any Python 3.10+ environment.
A practical guide for deploying AI-powered budget forecasting in a UAE government entity. Covers historical data requirements, model selection, scenario modelling, and how to present AI forecasts to non-technical leadership. Based on the PMO's FY2026 budget forecasting implementation.
Forecast government cloud demand and pre-empt capacity crunches with AI on your own telemetry.
Surface unusual network and access patterns across government systems for the security team to triage.