Saudi Vision 2030: Smart City AI Platform for NEOM Ecosystem Partner
Representative project: How we build sovereign AI platforms for smart city initiatives—typical scale: 50M+ daily events
About the Client
This capability demonstration shows how Hyperion builds enterprise AI platforms for smart city and national transformation initiatives. Based on our edge-to-cloud architecture methodology.
Size: Typical client: 500-5,000 employees
The Challenge
Build an enterprise-grade AI platform to process smart city sensor data and deliver real-time predictive analytics for infrastructure management.
Process 50M+ daily events from IoT sensors across smart building, transportation, and utility systems
Deliver sub-second predictions for energy optimization, traffic flow, and maintenance scheduling
Integrate with legacy SCADA systems and modern IoT protocols while maintaining security
Comply with Saudi SDAIA data governance requirements and prepare for international expansion
Enable Arabic-first AI interfaces while supporting multilingual operations
Design for extreme climate conditions (45°C+) with edge processing requirements
Our Solution
Designed and implemented a multi-layer AI platform with edge-to-cloud architecture, specialized Small Language Models for Arabic processing, and real-time analytics engine.
Built a sovereign AI architecture that keeps sensitive data within Saudi Arabia while leveraging cloud scalability for non-sensitive workloads. Deployed specialized SLMs (fine-tuned Phi-4) for Arabic language processing at the edge, enabling low-latency responses without external API dependencies. Created a unified data platform that normalizes diverse IoT protocols into a consistent analytics layer.
Implementation Phases
Architecture & Data Strategy
Designed hybrid edge-cloud architecture meeting SDAIA data sovereignty requirements. Created unified data model for 15+ IoT protocols. Established security framework for critical infrastructure.
3 weeksEdge AI Infrastructure
Deployed edge computing nodes with custom SLM for Arabic NLP, optimized for 45°C+ operation. Built offline-capable processing for critical functions. Achieved <50ms inference latency.
5 weeksCloud Analytics Platform
Implemented real-time streaming analytics (Apache Flink) processing 50M+ events/day. Built predictive models for energy optimization (12% reduction) and predictive maintenance (87% accuracy).
4 weeksIntegration & Localization
Integrated with existing SCADA and BMS systems. Deployed Arabic-first dashboard with RTL support. Trained local team on platform operations and model maintenance.
4 weeksTechnologies & Approaches
Results & Impact
Delivered a production AI platform processing 50M+ daily events with 99.9% uptime, achieving 12% energy cost reduction and 87% predictive maintenance accuracy.
“This representative project showcases our expertise in building sovereign AI architectures for national transformation initiatives. Edge-to-cloud systems with Arabic-first interfaces require deep understanding of both technical and cultural requirements.”