AI Ready Compute
Private GPU workspaces and sovereign compute environments for running AI workloads securely and independently.
What This Solves
Lack of secure, compliant environments for AI workloads
Many organisations need GPU compute for development, experimentation, or analysis — but cannot use generic cloud environments due to data sensitivity and compliance requirements.
No safe place to experiment with AI models and workflows
Teams often lack a controlled workspace where they can build, test, or run models without exposing data to unmanaged machines or shared infrastructure.
Operational risk from unmanaged local tooling
Data scientists and engineers frequently run workloads on personal devices or isolated servers, creating governance, security and consistency challenges.
Fragmented or inconsistent development setups
Without a standardised environment, teams face dependency issues, version drift, and unpredictable runtime behaviour.
How Arion Node Helps
Provides a private, isolated GPU workspace
Each Node is delivered as a dedicated container with isolated networking and optional encrypted storage — ensuring sensitive workloads remain contained and compliant.
Offers a ready-to-use AI development environment
Nodes come preconfigured with:
- CUDA-ready OS
- Python + Torch ecosystem
- JupyterLab (optional)
- Model inference tooling
- vLLM support
So teams can start working immediately with no setup overhead.
Supports any AI or ML workflow you need
Use Arion Node for:
Managed through the Arion Flow control plane
Provision, start, stop and lifecycle-manage Nodes using the same unified interface that powers Mnemo, Lumen, Athena and Nexus — no separate tools required.
A bridge toward sovereign and on-premise AI infrastructure
Nodes enable organisations to build experience with GPU workloads today while maintaining alignment with future plans for sovereign or in-house deployments.
Example Real-World Applications
AI research and experimentation
Create a secure GPU lab for data science teams to test models, explore datasets or validate approaches.
Notebook-driven analysis
Run Jupyter notebooks safely for data analysis, embedding generation, feature engineering or structured evaluation.
Batch processing
Use Nodes to run large-scale inference workloads, structured processing, or evaluation pipelines in a controlled environment.
Custom agent development
Develop and test agentic automation, retrieval workflows, or internal AI tools before moving to production.
Dataset preparation
Clean, transform and structure training datasets prior to using Arion Athena.
Internal environments
Offer dedicated GPU workspaces for internal AI teams, partner organisations, or customer-facing managed services.
Why Organisations Choose Arion Node
Plan an Arion Node Deployment
A clear and simple path to secure compute: