Archon + NVIDIA NIM
Archon routes managed AI workforce tasks to NVIDIA NIM through NVIDIA API key, private endpoint, or Kubernetes access. Agents use enterprise gpu inference, private model serving, optimized endpoints, governed by model policy, evals, fallback rules, usage controls, and audit logs.
AI Models
How Archon uses NVIDIA NIM.
Teams use this model layer to route agent work to the right inference environment: frontier APIs for the hardest reasoning, managed model gateways for enterprise controls, and local or private runtimes when data boundaries, latency, or cost require it.
Enterprise GPU inference
Private model serving
Optimized endpoints
Secure operating layer
Governed access, by default.
Model access is governed like any other production dependency. Archon scopes model policy, prompt boundaries, logging, fallback behavior, evals, cost controls, and where inference is allowed to run.
Model policy and routing
Archon defines when NVIDIA NIM should run, what context it can receive, which tools it may call, and where fallback models take over.
Evals and release checks
Every production workflow gets quality gates, regression checks, hallucination review, and escalation paths before expansion.
Usage and audit controls
Token use, latency, prompts, retrieval context, model responses, and reviewer decisions are visible in the command center.
Related integrations
More in AI Models.
FAQ
NVIDIA NIM questions.
How does Archon connect to NVIDIA NIM?+
Can NVIDIA NIM run privately or locally?+
How does Archon decide when to use NVIDIA NIM?+
Get started
Put NVIDIA NIM into a governed model routing plan with Archon.
Bring the workload, data boundary, latency target, quality bar, and approved deployment environment. We will map the model route, controls, evals, and first production workflow.