ALNETS

ALNETS · Deployment guides

Agent host and model inference: separate the runtime from compute

An Agent host runs the client, tools and task workspace. Inference comes from a centralized API gateway or local model service. Decoupling the runtime ensures clean cost control.

AI infrastructure·⏱ 5 min read
⚡KEY TAKEAWAYS · TL;DR

Short answer

Treat the Agent host as a dedicated task runtime, not model training or inference hardware. Decide where the model runs, then plan the client host, model service and network separately.

What the Agent host does

The host runs the Agent client, tools and task directory in a dedicated user environment. For enterprise use, plan one host per user. Configure accounts, tool permissions and data access to organizational requirements.

  • Confirm clients, tools and dependencies.
  • Define work directories and enterprise data boundaries.
  • Define interruption, output-saving and human-intervention handling.

Choose an inference path

PathConsiderationsArchitecture Benefits
Unified API Gateway Cloud InferenceAn external model service is authorized via gateway.Centralized token auditing; keys never touch edge PCs.
Local Edge Model ServiceSensitive enterprise data must remain on LAN.Sub-second latency with zero WAN bandwidth cost.

Keep connectivity in scope

AiR is optional, depending on external-connectivity needs. The local LAN directly carries calls to on-prem model services; when calling external models, AiR and the enterprise API gateway provide secure tunneling.

ARCHITECTURE & HARDWARE SYNERGY

Recommended Products & Bundles

Hardware appliances, gateways, and collaborative suites referenced in this guide: