Self-hosted AI automation, unmetered.
Run AGNT on the desktop, on a home server, or in a container on infrastructure you already pay for. There is no execution ceiling, no per-task counter, and no tier that unlocks the ability to run your own automation more often.
Same runtime, different footprint
Workflows and agents are portable across all three. Build on the desktop, move to a server when the work needs to run around the clock.
Windows, macOS, Linux
The full application with the visual builder, agent workspace, and marketplace. The fastest way to start — install and run, no account required.
Containerized
Run headless in a container on a NAS, a VPS, or your own cluster. Ideal for scheduled and webhook-triggered work that should not depend on a laptop being awake.
AGNT-hosted cloud
If you would rather not operate it, paid tiers run the same runtime for you with encrypted vault sync and 24/7 execution.
# Pull and run headless — persist state to a local volume docker run -d --name agnt \ -p 3000:3000 \ -v ./agnt-data:/app/data \ --restart unless-stopped \ ghcr.io/agnt-gg/agnt:latest # With a local model — no data leaves the host docker compose up -d # agnt + ollama, see the docs for the compose file
Current image tags, compose files, and environment variables are documented in the setup guide.
Why unmetered changes what you automate
Per-task pricing shapes behaviour
When each run costs money, you ration automation. The work that gets automated is the work expensive enough to justify the meter — which excludes most of the small, frequent, genuinely annoying tasks.
- High-frequency polling becomes uneconomic
- Retries and error handling cost extra
- Testing a workflow consumes production budget
- Success is penalised — more volume, higher bill
Owning the runtime removes the question
Local execution has no marginal platform cost, so the only question is whether the automation is useful — not whether it clears a per-run price.
- Poll every minute if that is what the job needs
- Retry aggressively; failures are free
- Test as much as you like before shipping
- Scale volume without scaling platform spend
What you do still pay for
Model inference. If you route to a hosted provider, that provider bills you directly for tokens — AGNT does not mark it up or sit in the middle. Route to a local model through Ollama or LM Studio and that cost goes to zero as well, at the price of running the hardware yourself.