Inference is the compute and model-service layer the whole suite calls into — heterogeneous pools governed honestly, serving with guardrails.
Accelerators from different vendors and models are managed in one control plane — each pool operates independently without interference, and compute status is fully visible. Nothing is disguised as a single resource it is not.
An industry-standard way to call models: existing applications integrate almost unchanged, and the underlying hardware is invisible to them. Plug in and start serving.
Onboarding, go-live, upgrade, scale and rollback are managed end to end — running services stay stable without interruption, and every change is controlled and reversible.
Fine-tuning and training run as managed tasks on the same platform as online services, with progress always visible — no more ad-hoc scripts, and every training output is archived uniformly.
Who can call, how much they may call and what it costs are unified under identity and permissions. Every call is attributable, metered and audited — costs are always in view.
Fully offline installation, upgrade and rollback, with on-site diagnostics and acceptance — deliverable even in air-gapped environments, so compute capability lands reliably.
Different hardware pools are never disguised as one physical resource pool — each pool is operated independently, reconcilable, observable and rollback-able.
Ascend and Hygon are scheduled and certified separately — no cross-pool sharding.
Cohort / Studio / RAGFlow all call the TUEO Endpoint, not their own providers.
Resource allocation and business access, usage and audit in one closed loop.
Air-gapped deployment, upgrade and rollback, diagnostics and on-site acceptance.
Book a demo to discuss your compute pool, model serving or private-inference requirements.