AI agent servers
An AI agent server is a machine that runs coding agents and automations around the clock. Agents run long jobs, call tools, touch files and reach the network unattended, so reliability, remote access, isolation and logging matter as much as the GPU. Sometimes a modest machine is enough.
When it fits
The right choice when
- Agents run for hours or around the clock, unattended.
- They need local models for privacy, cost or offline work.
- Several developers or workflows share the same machine.
- You want logs of what agents did and when.
Look elsewhere when
- Your agents only call cloud model APIs: a modest CPU machine or a container host may be all you need.
- Agents run occasionally on a developer's own laptop.
What decides the configuration
The variables we work through with you before recommending anything.
| Criterion | Why it matters | What we check |
|---|---|---|
| Uptime and restart | An unattended machine must come back on its own after a power cut. | UPS, auto power-on, service restart behaviour. |
| Remote access | Someone will manage it from elsewhere, safely. | VPN or existing gateway; no open ports to the internet. |
| Isolation | Agents run code and commands; mistakes should stay contained. | Containers or VMs per agent, limited permissions. |
| Logging and monitoring | You need to see what agents did and spot runaway jobs. | Central logs, resource alerts, retention. |
| Model serving | Local models need GPU memory; API-only agents do not. | Which steps run locally and which call cloud APIs. |
| Storage and backups | Agents create code, artifacts and state worth keeping. | Mirrored disks, snapshots, backup destination. |
An agent server is a service, not just a fast GPU
What agents do differently, and what that means for the machine.
They run long
Jobs take hours, so the machine is planned for sustained load and recovery after interruptions.
They act
Agents execute commands and edit files, so each one runs isolated with only the access it needs.
They talk to the network
Repositories, APIs and package registries: traffic is allowed deliberately, not by default.
They need watching
Logs and alerts show what happened overnight and stop a runaway job from filling the disk.
Reference builds
Configuration examples to start from. Every one is validated against your workload before quoting.
GPUs we build with
Related guides
Common questions
Do agents need a GPU at all?
Only for models you run locally. If your agents use cloud model APIs, a reliable CPU machine with good storage may be enough, and we will say so.
Can it run in an office?
Yes, a tower can. We choose components for continuous office operation and plan for power cuts.
How do we keep agents from doing damage?
Each agent runs in its own container or VM with limited permissions and network access, and its actions are logged. We set this up with you.
What does it cost to run 24/7?
Mostly electricity, which depends on the GPU and load. We estimate power draw for your configuration during the consultation.
Plan an always-on agent machine
Tell us what your agents do and which models they use. We will size it, or tell you when a smaller machine is enough.