Accelerate scientific discovery with scalable GPU computing and sovereign AI infrastructure for universities, research institutions and innovation ecosystems.
RE:AI. Empowering the Next Breakthrough in AI Research and Innovation.
Research organisations increasingly rely on AI to accelerate scientific discovery, analyse complex datasets and drive next-generation innovations. High-performance GPU computing enables researchers to train models faster, run larger simulations and reduce the time required for breakthrough discoveries. RE:AI provides scalable AI infrastructure that helps researchers move from experimentation to real-world impact.
Illustrative Use Cases
Foundation model training
Train sovereign large language models (LLMs) and multimodal models on secure local infrastructure.
OUTCOME
Faster model development, data sovereignty, scalable
compute access.
<p>Deploy AI securely while maintaining control over data and governance. </p>
Scalable GPU computing
<p>Access high-performance GPU resources on demand. </p>
Enterprise AI platform
<p>Develop, deploy and manage AI workloads through a unified platform. </p>
Trusted ecosystem
<p>Access leading AI technologies and expertise through a robust ecosystem of partners. </p>
Production-ready AI
<p>Move AI projects from proof of concept to enterprise deployment faster.</p>
Frequently Asked Questions
How can AI accelerate research and discovery?
AI can help researchers analyse complex datasets, generate hypotheses, navigate existing research and explore new areas of investigation. It can also support research workflows such as patent analysis and grant proposal development.
Why do research institutions need scalable AI infrastructure?
Research workloads can involve large datasets and computationally intensive AI models. Scalable AI infrastructure gives researchers access to the processing capacity needed to experiment, iterate and expand workloads as research requirements grow.
Why is GPU computing important for AI research?
High-performance GPUs accelerate computationally intensive AI workloads such as model training, inference, simulations and data analysis. On-demand GPU computing gives research teams the flexibility to access additional processing capacity when required.
How can sovereign AI infrastructure protect research data and intellectual property?
Research can involve sensitive datasets, proprietary methods and valuable intellectual property. Sovereign AI infrastructure gives institutions greater control over where research data and AI workloads are processed and how they are governed.
How does RE:AI support AI research and innovation?
RE:AI supports AI research and innovation with sovereign AI infrastructure, high-performance GPU computing, enterprise connectivity, Nxera’s AI-ready data centres and Paragon orchestration, giving research teams scalable resources for demanding AI workloads. This helps researchers experiment, analyse and advance their research without having to build and manage the underlying AI infrastructure.
