Cloud-independent core
Architecture intended to support normal AI inference and local knowledge workflows without a live internet connection.
Autonomous AI hardware engines designed to operate locally — keeping intelligence close to your people, processes and data. No cloud required for core AI workloads.
AXRYXCloud AI has its place. But sensitive engineering information, isolated sites and critical operations deserve a different option: an AI system you can own, run and control.
Architecture intended to support normal AI inference and local knowledge workflows without a live internet connection.
Keep documents and model execution inside your chosen computing environment, with access controls and local data-handling policies.
Move beyond chat to configured workflows and agent-assisted tasks, with appropriate authorisation and human review.
Three proposed configurations, from local engineering assistants to higher-capacity enterprise computing. Final specifications and availability will follow prototype validation.
A departmental system concept for engineering workflows, shared AI assistance and controlled autonomous agents without relying on cloud inference.
AXRYX X5LOCAL AI ENGINEProduct names, system images and configurations are illustrative; no shipping specifications or performance claims are implied.
AXRYX is being designed as an integrated computing environment — from the physical AI engine to the model runtime, technical knowledge layer and carefully governed autonomous agents.
Explore the architecture ↗Our initial focus is on organisations whose information is valuable and whose operations cannot always depend on the cloud.
Controlled technical document search, troubleshooting assistance, quality knowledge and production workflows.
Explore applications ↗Offline engineering support, approved knowledge retrieval and isolated technical workflows.
Explore applications ↗Local AI assistance for sensitive data, remote sites and environments with controlled connectivity.
Explore applications ↗Early AXRYX engagements will focus on one valuable, measurable application before broader deployment.
Identify your workflows, data sensitivity, users and connectivity constraints.
Align the hardware concept, AI models and local knowledge sources.
Agree accuracy, performance, security and offline-operation acceptance tests.
Move ahead only when the system demonstrates the required value and controls.
Exploring local AI for your organisation? Talk to us about the use case, constraints and opportunities.