A setter closes strangers.
Who answers your roster?
An AI setter qualifies the people in your DMs who have not paid you and books the call. That is genuinely useful, and it is half of what your inbox does. Amped works the other half too — the clients already paying you — without ever letting the two get the same reply.
What an AI setter actually does
A setter is the role that works inbound leads before they ever reach a sales call. They answer the first message quickly, find out whether someone is a fit, handle the early objections, and get the call in the calendar. Coaches have hired for this for years, and it is expensive enough that most never do.
An AI setter does that job in your DMs automatically: replies within a minute around the clock, asks your qualifying questions rather than generic ones, and books onto your calendar. When it is done well it is a real improvement over a lead sitting unread until Sunday night.
The half of the inbox it was never pointed at
Every tool in this category is aimed at the same person: a stranger who has not paid you. That is deliberate and it is fine — but it means the moment someone buys, they leave the system entirely and become your problem again.
Which is the wrong way round, because that is when the messages get harder. The client mid-programme asking whether to deload, or what to swap a movement for, or why the numbers moved — those need the programme you wrote them, and a setter was never given it.
Worse, a setter meeting a client tends to do something actively bad: it qualifies them, or pitches an offer they already bought. Nothing says a coach has lost track of you faster.
Both jobs, kept apart on purpose
Amped checks which thread it is in before it decides how to answer. A confirmed client is answered out of your uploaded material — your videos, PDFs, programmes and coaching notes. A lead is not, and not because the model was told to decline: for anyone unconfirmed, that material is never retrieved in the first place, so it is not in context to be talked out of.
The lead still gets a genuinely useful reply and a reason to book. Why the two jobs need separating, and what the replies look like in a real thread.
Either side can run in Draft Mode, where every reply waits for your approval, or on Autopilot — set per channel, and reversible on the next message. Coming from a flow builder instead of a setter? How Amped compares to ManyChat.
AI setters, answered
Your DMs are already piling up.
Your AI should be handling them.
Train your AI, connect Instagram and SMS, and let Amped handle the inbox while you focus on coaching.
We’re onboarding coaches in small groups. You’ll build and test your AI before it sends anything.