An agent built for one job.
When the work is specific, a general assistant is the wrong shape. A custom agent gets a defined mission, your data, a fixed set of actions, and one measurable outcome.
What actually changes
A generic assistant that does everything vaguely.
One agent that does one job properly.
Nobody can say what the AI is allowed to do.
Its actions are an explicit list.
You cannot tell whether it helped.
It is measured on a business outcome.
What it does today
- Defined mission and scope
- Connected to your data sources
- An explicit list of permitted actions
- Cooperates with the other agents through the Core
- Measured against a stated outcome
Still in development
- Self-directed multi-step planning
- Agents that commission other agents
Listed so you know what you are not buying yet.
Follow-Up Agent — Chases what nobody has time to chase.
Illustrative agent roles.
How it happens
- 1Name the job
If it cannot be stated in a sentence, it is more than one agent.
- 2Draw the boundary
What it may read, and what it may change.
- 3Connect it
To the same memory the rest of the Core uses.
- 4Measure it
One number that tells you whether it is worth keeping.
Connects to
- Phone / Voice
- Website chat
- Messenger
- Telegram
- SMS
- Google Calendar
- Google Sheets
- Excel / CSV
Straight answers
How is this different from the other products?
They are the common jobs, already built. This is for the job that is specific to you.
Can it act without asking?
Only where you decide it may. Everything else runs with approval.
It works better with the rest of the Core.
Each product is useful alone. They share one memory of your customers, which is where the value compounds.
Book an AI audit