Docs: How Maritime works, agents, sleep and wake | Maritime

How Maritime works

The mental model behind every other page in these docs, on one page. Five minutes here saves an hour of guessing later.

Maritime gives your agents the computers they need: Linux sandboxes, Linux and Windows desktops, and Android phones, each its own isolated machine that sleeps (or, for a sandbox, ends) when idle and starts again on demand. The machines have their own pages, starting with Agent boxes and Linux desktops. This page covers the agent you run on them: what it is, how it sleeps and wakes, how it reaches a model, and what it costs.

The shape of an agent

Its own micro-VM, with its own kernel.

A disk under /data that outlives sleep and redeploys.

An agent is a long-lived program running in its own isolated VM (a sandboxed container) with four things attached:

Sleep and wake

A machine sleeps when idle and wakes in about a second on the next request. An agent box costs the same awake or asleep.

Agents sleep when idle and wake when needed. This is the core economic idea: you can keep hundreds of agents around because each one costs $1 a month per 2 GB of memory, awake or asleep, and a sleeping agent loses nothing.

maritime sleep pauses the agent, maritime list shows it sleeping, and the next chat message wakes it from a VM snapshot. The lifecycle logs time each wake at 1.1 to 1.4 seconds.

One consequence worth internalizing: timers inside a sleeping agent do not fire. Scheduled work belongs in a platform trigger, not an in-process scheduler. That is what Triggers & schedules is for.

Projects and the front door

One machine per person: each of your users gets their own agent or computer, keyed by your own id.

Every agent lives in a project (its projectId is on the agent object). Channels attach at the project level: point a Telegram bot at a project and it becomes the front door for the agent inside it. With the project's newChatPolicy set to spawn, each new person who messages the bot gets their own agent instance, which is the same mechanism the SDK uses to give every customer of your product their own agent.

How agents reach a model

Hosting and model calls are separate. For LLM access there are two paths:

What it costs

One subscription covers every machine. Your monthly plan fee (Starter $20, Growth $100, Scale $500, Dedicated $5,000, or Enterprise) becomes usage credit. An agent runs in an agent box, billed per second at $1 a month per 2 GB of memory, awake or asleep. Other machines are billed per second at their hourly rates while awake, and for their disk while asleep. Usage past the credit is billed on the same invoice. New accounts start with a 7-day free trial with up to $20 of usage. Model calls through the proxy are paid separately, from prepaid AI credits. Full tables in Billing & plans.

Five ways to drive it

Next

Deploy your first agent in the quickstart, pick a template on Choose a framework, or wrap your own code with Deploy any container.