End-to-end data platform modernization, AI/ML engineering, and business intelligence services — designed for enterprises across the Middle East and beyond.
Six integrated practice areas covering the full data lifecycle — from platform design and migration to AI operationalization and governance.
Design and build modern cloud-native data platforms — data lakes, lakehouses, and enterprise data warehouses on Azure, AWS, or GCP with medallion architecture patterns.
End-to-end ML engineering — from data preparation and model development to training, deployment, and monitoring. Generative AI integration with Azure OpenAI and custom LLM solutions.
Transform raw data into actionable insights with modern BI platforms. Interactive dashboards, self-service analytics, embedded reporting, and real-time KPI monitoring.
Establish enterprise data governance frameworks — data cataloging, lineage tracking, quality management, and compliance with NCA, SAMA, PDPL, and international standards.
Migrate on-premises databases, data warehouses, and ETL workloads to the cloud. Build real-time and batch integration pipelines connecting disparate enterprise systems.
Implement DataOps practices for continuous data delivery. Infrastructure as code, CI/CD for data pipelines, automated testing, monitoring, and cost optimization.
A proven five-phase approach that takes you from data strategy through to operational AI — with governance embedded at every stage.
Map your current data landscape — sources, volumes, quality, governance maturity, and stakeholder needs. Identify quick wins and build a prioritized roadmap aligned with business outcomes.
Design target-state data architecture — storage layers, compute patterns, integration topology, security model, and governance framework. Select technology stack and define data models.
Implement data pipelines, transformation logic, and storage layers. Migrate existing workloads, build integration connectors, and establish CI/CD for data platform components.
Develop BI dashboards, semantic models, and AI/ML solutions. Train and validate models, build generative AI applications, and deploy analytics to business users.
Deploy to production with monitoring, alerting, and auto-scaling. Establish data governance policies, quality rules, access controls, and knowledge transfer to your team.
A reference architecture for enterprise data platforms — from ingestion through governance, designed for scalability and compliance.
Practical applications of data and AI across industries — from predictive analytics to intelligent automation and regulatory compliance.
Real-time business performance monitoring with Power BI and Tableau — connecting ERP, CRM, and operational data into unified executive views.
ML models that predict equipment failures before they happen — reducing downtime and maintenance costs for manufacturing and energy sectors.
AI-powered extraction and classification of Arabic and English documents — invoices, contracts, government forms — using Azure AI Document Intelligence.
Analyze cloud and SaaS license utilization data to identify waste, right-size subscriptions, and forecast spending with data-driven FinOps.
Automated compliance monitoring against NCA, SAMA, and PDPL — with audit-ready dashboards and gap analysis reports for Saudi regulators.
Custom generative AI assistants built with Azure OpenAI and RAG patterns — grounded in your enterprise knowledge base for internal support, HR, and IT.
Unified customer profiles by consolidating data from CRM, web, social, and transactional systems — enabling personalization and churn prediction.
Migrate on-premises SQL Server, Oracle, or Teradata warehouses to modern cloud platforms — preserving business logic while reducing cost and complexity.
We work across the Microsoft Azure ecosystem and leading data platforms to deliver solutions tailored to your environment.
Synapse, Fabric, Data Factory, Azure ML, Purview, Power BI
Lakehouse, Spark, MLflow, Unity Catalog, Delta Lake
Cloud data warehouse, data sharing, Snowpark
GPT-4, embeddings, RAG, Copilot Studio, AI Search
Dashboards, semantic models, paginated reports, embedded
Infrastructure as code, CI/CD, DevOps, platform automation
Analytics engineering, data transformation, testing, docs
Data governance, cataloging, lineage, sensitivity labels
From data strategy and platform modernization to AI deployment and governance — our team is ready to accelerate your data-driven transformation.
