Make compute an implementation detail.
NodeAI connects authenticated compute nodes to an AI runtime and makes routing, fleet controls, policy, evaluation, and optimization part of the same operating layer. Your application asks for inference; NodeAI selects eligible compute.
Authenticated nodes · policy-aware routing · fleet governance · measurable optimization
Resilient Intelligence
The conversation survives the hardware.
NodeAI treats your inference session as a permanent state, independent of the underlying compute.
Hardware-Independent Streaming
The conversation survives the compute. When active compute drops mid-response, NodeAI can continue the session on eligible alternate compute without restarting the conversation or changing its trust boundary.
Resilient Session
The session is designed to remain resilient when underlying compute changes. When active compute becomes unavailable, NodeAI can continue the persisted conversation on eligible alternate infrastructure without changing its configured security or compliance requirements.
Boundary-Locked Switching
Models can change without lowering the security or compliance requirements attached to a conversation. A model that cannot satisfy those requirements is not used.
Context-Adapting Runtime
NodeAI adapts conversation context to the selected model’s capacity and clearly signals when context must be reduced, rather than failing silently.
Enterprise controls
Enterprise controls available today.
Authenticated compute nodes
Connect approved machines with durable trust, health, capability, and account-scoped ownership controls.
Multi-node fleet
Register multiple compute nodes per account and track trust tier, lifecycle, compliance, runtime, load, reliability, and performance signals.
Policy-aware routing
Select eligible compute using model support, sensitivity, trust tier, compliance, latency, cost, quality, and current load.
Fail-safe operations
Quarantine or revoke a node immediately so it is removed from routing, with an auditable record of the decision.
Governance + audit
Persist workspace-ready policy, approved model constraints, audit events, node controls, and data-sensitivity boundaries.
Evaluation + feedback
Store ratings, corrections, evaluation sets/results, replay metadata, and node/model measurements so routing decisions have an evidence trail.
Cost-aware compute
Track node economics and provider/model rates, then include estimated cost in route selection and optimization gates.
Production optimizer
Evaluate compute and model candidates using quality, latency, and cost signals, with explicit and auditable optimization decisions.
Mid-conversation model switching
Change the model inside a live conversation, once or persistently, while preserving the conversation’s configured security and policy requirements. Conversation context carries forward, with clear handling when the selected model has less context capacity.
Shadow routing
Run a second candidate node or model alongside the primary for controlled comparison of latency, cost, quality, and reliability. Shadow workloads remain subject to the same sensitivity, security, compliance, and approved-model requirements.
Hardware-independent streaming
Continue a live session on eligible alternate compute when active compute becomes unavailable, preserving the conversation’s configured security and compliance requirements.
Trust-aware routing
Data sensitivity changes the compute pool.
Routing evaluates security, sensitivity, compliance, and lifecycle requirements before cost or performance. Sensitive and regulated workloads can restrict the available compute pool, after which cost and performance help select among eligible options.
Model changes and shadow evaluations remain subject to the conversation’s configured security and compliance requirements. Model availability never overrides those requirements, and shadow workloads cannot run outside the primary workload’s approved policy boundary.
Resilient sessions
Keep a session independent from a single compute node and continue on eligible alternate compute when a node fails.
Session recovery and resilience
Track continuation and recovery state without weakening the session trust boundary.
Live fleet control
See multiple authenticated workstations, availability, health, capabilities, lifecycle, compliance, and routing signals from the registered chat.
Operator feedback
Rate responses and run policy-bound shadow comparisons from the same runtime surface so evaluation evidence stays attached to the session.
Compute node failure
A node can die mid-generation. The conversation doesn’t.
When compute serving a live generation becomes unavailable, NodeAI can continue the session on eligible alternate compute while preserving the conversation’s configured security, sensitivity, and compliance requirements. Recovery does not silently lower the workload boundary.
Detected mid-stream
Failure is detected during the active response so NodeAI can begin recovery while preserving the session and its configured policy boundary.
Security requirements preserved
Alternate compute must satisfy the workload’s configured security and compliance requirements. High-sensitivity workloads are not moved to infrastructure that does not meet those requirements.
History carries over
The persisted conversation remains available after a compute change, so the session can continue without requiring the user to start over.
Shipped, not promised
The pieces you can build against today.
Compute Agent
Turn a machine into an authenticated NodeAI node.
The Compute Agent securely connects approved infrastructure, reports health and capabilities, and executes workloads under your policies. Approved compute provisioning is available through NodeAI.
Install the Compute Agent, connect approved compute, and manage it from NodeAI.
Download Compute Agent