AcornReply
AI customer service agent

An AI agent that drafts. A human who sends.

The phrase "AI customer service agent" covers two very different products: an autonomous agent that answers your customers on its own, and an AI assistant working alongside a human agent. AcornReply is the second kind. If what you want is the first, Intercom Fin and Zendesk AI resolution are the honest answer, and this page will not pretend otherwise.

The problem

When one person is the entire support team.

Most teams searching for an AI agent are not trying to remove humans from support. They have one human, that human has three other jobs, and the queue keeps arriving anyway. The question is whether a second pair of hands has to be a hire.

  • One person is the whole support team.

    Support is one job among four. Writing a good reply takes real time, and that time is the first thing squeezed by everything else on the calendar.

  • The queue does not stop for a meeting.

    An hour in a call is an hour of customers waiting, because there is no second agent to cover the gap and no shift to hand over to.

  • Hiring a second agent is a large step.

    A support hire means a process, a permanent cost and a training period, all for a queue that might need two focused hours a day.

How AcornReply solves it

What "agent" means inside AcornReply.

It behaves like a second agent who writes quickly and never sends without you. It reads the message, finds the answer in your own help center, and hands you a finished draft. You remain the person your customer is talking to.

  1. The AI drafts as though it were your second agent.

    Every inbound message arrives with a full reply already written, not a suggestion chip and not a sidebar you have to prompt into usefulness.

  2. It answers from your help center, not from a generic idea of support.

    Drafts are grounded in your own articles, FAQ entries and past replies, so the answer sounds like your team and cites the page it came from.

  3. A human always sends.

    Out of the box nothing leaves the workspace without a person approving it. Auto-reply exists, it is opt-in, and it is off by default.

  4. You keep the customer relationship.

    The customer gets a normal email from your address. There is no bot persona in the thread and nothing to disclose, because a person really did send it.

Example

A morning with a second agent.

Eleven messages overnight. Nine of them are questions your help center already answers, and all nine are drafted before you open the inbox. You read, adjust two, and send. The remaining two are the ones that needed you: a refund edge case and an angry customer. Those get your full attention, because the other nine did not take it.

Getting started

Your first reply, in five minutes.

Sign up, forward your support address, paste five past replies. The next inbound message arrives with a draft already written.

Frequently asked questions

What is an AI customer service agent?

The phrase covers two products. One is an autonomous agent that answers customers directly and resolves tickets without a person, which is what Intercom Fin and Zendesk AI resolution do. The other is an AI assistant sitting next to a human agent, drafting the reply that the human then sends. AcornReply is the second.

Can an AI agent reply without a human?

In AcornReply, only if you switch auto-reply on. It exists, it is opt-in, and it is off by default, so out of the box every reply waits for a person. If autonomous resolution is what you actually want as the normal path, buy a product built around it rather than turning ours into one.

Will an AI agent replace my support hire?

It postpones one. Drafting takes most of the minutes out of each reply, so a team of three can hold a queue that would otherwise need a fourth person. It does not remove the judgment calls, and it does not cover a queue that needs staffing around the clock.

How does the AI know my product?

From your help center articles, your FAQ entries and the replies you have already sent. You pick a voice profile at setup and it tunes toward how your team writes as you send. There is no prompt writing and no model training on your side.