Introducing
Project Genesis

Uvation’s global initiative to develop nuclear-powered infrastructure for frontier AI.

Project GENESIS is designed to help organizations deploy interconnected AI factories across the regions their operations require. Bringing compute, power, cooling, connectivity, and automation into a vertically integrated model, the project aims to support scalable AI capacity across multiple locations, connected for real-time communication and coordinated operations.

Multi-modal Ai

Key Capabilities

Dedicated behind-the-meter nuclear power.

On-site micro-reactors provide a power foundation for AI operations, supporting sustained compute demand and eliminating dependence on traditional grid and reducing geographical constraints.

End-to-end planning and delivery.

Uvation ties together planning, design, deployment, and operations, coordinating supply chain partners and specialist providers to meet infrastructure requirements.

Global Deployment Expertise.

Project Genesis deploys across the US, Canada, Brazil, Europe, the GCC, and Asia, adapting common AI factory blueprints to local regulations and customer demand.

Multi-modal Ai

Key Capabilities

Dedicated behind-the-meter nuclear power.

On-site micro-reactors provide a power foundation for AI operations, supporting sustained compute demand and eliminating dependence on traditional grid and reducing geographical constraints.

End-to-end planning and delivery.

Uvation ties together planning, design, deployment, and operations, coordinating supply chain partners and specialist providers to meet infrastructure requirements.

Global Deployment Expertise.

Project Genesis deploys across the US, Canada, Brazil, Europe, the GCC, and Asia, adapting common AI factory blueprints to local regulations and customer demand.

Era of scales

Global AI infrastructure aligned with your operations

An organization’s AI infrastructure must support both concentrated computing demand and applications distributed across its operations. Large-scale training, private AI platforms, and latency-sensitive inference each require a different balance of compute capacity, connectivity, and proximity to users and data.

Project GENESIS is designed around this range of requirements, combining centralized AI environments with modular factories and edge deployments. Terrestrial and satellite communications support its distributed compute architecture, while standardized infrastructure provides a foundation for regional expansion and long-term scalability.

Era of scales

Global AI infrastructure aligned with your operations

Our Models
Four Core Deployment Models

Uvation provides repeatable, modular, and  compliant AI infrastructure designed for frontier- scale compute.

Traditional Data Centers

Large Language Model (LLM) - Training and refinement

Enterprise AI Platforms and Private AI clouds

National and regional sovereign AI initiatives

Large-scale, high-density datacenter deployments optimized for sustained AI training and enterprise workloads.

Key Characteristics

High-power GPU clusters for foundation model training and fine-tuning
Support for sovereign AI, regulated enterprise, and government workloads
Integration with existing Tier III / Tier IV facilities
High-bandwidth networking and redundant power infrastructure

Explore Traditional AI Factory

Large Language Model (LLM) - Training and refinement

Enterprise AI Platforms and Private AI clouds

National and regional sovereign AI initiatives

Space & Ground Mesh Ecosystem

Global AI services requiring geographic reach and redundancy

Remote sensing geospatial intelligence, and telemetry processing

Defense, aerospace, and mission-critical AI applications

A distributed AI compute layer integrating space-based and terrestrial communication networks.

Key Characteristics

Interoperability with satellite, ground station, and terrestrial fiber networks
Resilient, fault-tolerant architecture for distributed inference and training
Designed for disconnected, intermittent, and low-infrastructure environments

Explore nuclear AI factory

Global AI services requiring geographic reach and redundancy

Remote sensing geospatial intelligence, and telemetry processing

Defense, aerospace, and mission-critical AI applications

Edge AI Sites (inference)

Real-time analytics, vision, and speech AI

Smart cities, autonomous systems, and industrial automation

Retail, healthcare, and financial services inference workloads

Low-latency inference Infrastructure deployed close to data generation and end users.

Key Characteristics:

Compact, power-efficient AI nodes optimized for inference workloads
Proximity to population centers, industrial zones, and data sources
Reduced backhaul costs and improved real-time responsiveness

Explore Datacenter

Real-time analytics, vision, and speech AI

Smart cities, autonomous systems, and industrial automation

Retail, healthcare, and financial services inference workloads

Modular AI Farms (Training)

Regional AI capacity expansion without long build cycles

Dedicated training environments for enterprise and sovereign customers

Temporary or burst training capacity aligned with off-take agreement

Containerised, rapidly deployable AI factories designed for scalable training and burst capacity.

Key Characteristics

Standardized containerized infrastructure enabling fast deployment
Modular scaling by SU units to match demand growth
Energy-aware design supporting dedicated and alternative power sources

Explore Modular AI factories

Regional AI capacity expansion without long build cycles

Dedicated training environments for enterprise and sovereign customers

Temporary or burst training capacity aligned with off-take agreement