What can an agent actually touch?

Exactly what you scope: per-folder file access, per-computer permissions, and an autonomy dial from read-only to full: nothing outside it.

What does a scheduled run cost?

Each run shows its cost, and delegated runs carry budget caps you set: a run stops at its cap instead of surprising you.

What happens when a run fails?

Failed runs aren't billed, the trace shows exactly where it stopped, and notifications tell you without you watching.

All use cases

Automation & ops

Give it to an agent.

Agents with memory, real computers they can drive, and schedules that run overnight.

Try now See pricing

Automation tools stop at API calls.

idapt agents drive real computers: terminals, files, browsers, desktops.

Brittle workflows break when a vendor changes something.

Agents reason through changes instead of failing on a hardcoded step.

Autonomy without oversight is a liability.

Ask-first autonomy by default, budget caps per run, and a full action trace.

Teach an agent your playbook

Instructions, skills, and memory: the agent starts every run knowing the job.

More about Agents

Give it a real computer

Terminals, files, and full desktops: cloud machines or your own, permission-scoped.

More about Computers

Put it on a schedule

Triggers chain chats, scripts, and notifications into a standing workflow.

More about Automations

Wake up to the result

Budget-capped runs finish in the background; the morning digest shows what happened.

More about Automations

What this replaces

node-based automation builders for AI-shaped workcron scripts nobody maintainsa VM you keep alive for one scheduled job

Built from these features

Agents

Skills, scoped permissions, persistent memory: any model you pick.

Computers

Daemon-connected machines with real filesystems and agent-friendly controls.

Automations

Delegated runs with schedules, bounded execution, and full progress traces.

Subagents

Parallel subagents, isolated context, full observability.

Memory

A durable, private memory every agent reads and updates as it works.

Tasks

Tasks Lists, multiple assignees, sub-tasks, blockers, and duplicates: clean OR-123 ids.

Frequently asked

Ready to work this way?

Create a free account and start in seconds.

Try now

All use cases

Automation & ops

Give it to an agent.

Agents with memory, real computers they can drive, and schedules that run overnight.

Try now See pricing

Automation tools stop at API calls.

idapt agents drive real computers: terminals, files, browsers, desktops.

Brittle workflows break when a vendor changes something.

Agents reason through changes instead of failing on a hardcoded step.

Autonomy without oversight is a liability.

Ask-first autonomy by default, budget caps per run, and a full action trace.

Teach an agent your playbook

Instructions, skills, and memory: the agent starts every run knowing the job.

More about Agents

Give it a real computer

Terminals, files, and full desktops: cloud machines or your own, permission-scoped.

More about Computers

Put it on a schedule

Triggers chain chats, scripts, and notifications into a standing workflow.

More about Automations

Wake up to the result

Budget-capped runs finish in the background; the morning digest shows what happened.

More about Automations

What this replaces

node-based automation builders for AI-shaped workcron scripts nobody maintainsa VM you keep alive for one scheduled job

Built from these features

Agents

Skills, scoped permissions, persistent memory: any model you pick.

Computers

Daemon-connected machines with real filesystems and agent-friendly controls.

Automations

Delegated runs with schedules, bounded execution, and full progress traces.

Subagents

Parallel subagents, isolated context, full observability.

Memory

A durable, private memory every agent reads and updates as it works.

Tasks

Tasks Lists, multiple assignees, sub-tasks, blockers, and duplicates: clean OR-123 ids.

Frequently asked

Ready to work this way?

Create a free account and start in seconds.

Try now