Front AI Pricing vs Per-Action AI: The Unit Economics (2026)

How Front prices its AI, as of capture

Front sells AI on top of its per-seat plans rather than baking all of it into the base price. The Front pricing tiers start with the seat cost itself — Starter at $25/seat/mo, Professional at $65/seat/mo, and Enterprise at $105/seat/mo on annual billing, as of capture — and then the AI capabilities layer on from there.

Some AI is included everywhere. Every plan ships with the lightweight tools: Topics, Compose (AI drafting, capped around 200 actions/day per Front's pricing page), Translate, and Summarize. These are the genuinely useful, low-stakes helpers, and it's fair to say Front gives them away well.

The heavier AI is where the meter starts. Per front.com/pricing, the add-ons break down like this, as of capture:

The pattern is clear: the agent (Autopilot) is metered per conversation, while the teammate assistants (Copilot, Smart QA) are metered per seat. That's a coherent design — but it's also where the unit economics get interesting.

Where native Front AI genuinely earns its keep

Before the comparison, credit where it's due. Front's AI is not a bolt-on afterthought — it's woven into the shared inbox, and for several jobs it's the right tool.

Compose and Summarize are free wins. Because they're included on every plan, a sales rep drafting a follow-up or an ops teammate catching up on a 40-message thread gets real leverage at zero marginal cost. There's nothing to justify to finance.

Copilot fits the collaborative model. Front is a shared-inbox platform built for teams working conversations together, and a per-seat reply assistant matches that shape — you're paying for the humans you already have, and they draft faster. For a tight support pod, $20/seat is a predictable line item.

Autopilot resolves the easy tail. For high-volume, low-variance questions — order status, hours, reset-my-password — an agent that closes the conversation without a human is exactly what you want, and paying per conversation feels fair when the conversation is genuinely simple.

The honest caveat is that Front's AI story has moved. AI Answers, Front's earlier answer bot, is now deprecated — its help center article carries a banner reading "AI Answers is no longer available for purchase. Check out Autopilot," per Front's own documentation. Autopilot is the successor, and if you're evaluating Front AI today, Autopilot and Copilot are the products that matter. For the full feature breakdown, Front AI explained walks through each one.

The unit-economics problem: what "per conversation" actually charges for

Here's the subtlety. Autopilot's "starting at $0.05/conversation" is a charge on the conversation it engages, not strictly on the problem it solves. And your automation rate — the share of conversations an agent can fully close without a human — is not a constant. It moves with your product changes, your seasonal question mix, your documentation quality, and how ambitious you get with what the agent attempts.

That variability is the crux. Consider two months with the same volume:

Under a pure per-conversation model, both months meter similarly on the AI side even though the value delivered halved. When outcomes are stable, per-conversation pricing is clean and easy to forecast. When outcomes swing — a launch, an outage, a policy change — you can find yourself paying for engagement on conversations that still needed a human. This isn't a knock on Front specifically; it's the structural nature of pricing an outcome-shaped tool on a per-unit meter.

How per-action credits change the math

A per-action model prices the individual step an AI agent takes — reading a conversation, calling a tool to fetch an order, drafting a reply, sending it — rather than the conversation as a billing unit or the seat as a subscription. Macha's credits are consumed per AI action, never per resolution. That distinction is the whole point: Macha is an automation and orchestration layer, and outcomes vary, so it prices the work the agent does, not a resolution it can't always guarantee.

The screenshot above shows a real Macha demo-org agent demonstrating per-action pricing — an agent model billed at "3 credits / message." It illustrates the per-action mechanic; Front is not a connected connector in this demo, so it does not depict a live Front conversation.

What changes when you meter per action:

1. Cost tracks work, not seats or guessed outcomes. A month with fewer AI touches costs less, automatically. You're not paying $20/seat for a teammate who barely used Copilot that week.
2. Simple and complex actions can be priced differently. A quick tag-and-route is cheap; a multi-tool workflow that pulls an order, checks a policy, and drafts a tailored reply costs more — because it is more. That's honest pricing for AI agents in customer service.
3. You control the aggression. Because you're paying per action, you decide how much reasoning to spend on which queues, rather than accepting a flat per-conversation rate across everything.

The comparison isn't "cheaper" versus "more expensive" — it's which risk you'd rather hold. Per-seat and per-conversation pricing shift variance onto you when outcomes drop. Per-action pricing keeps cost tied to the actions taken, which is easier to reconcile when your resolution rate is genuinely moving.

Front AI vs a per-action agent layer: the honest split

The right read isn't "replace Front AI." It's a division of labour. Keep Compose and Summarize — they're free and good. Use Copilot where per-seat assist genuinely helps your team. Then, for the reasoning-heavy, tool-calling, outcome-variable work, add an agent layer that prices per action so your bill follows the work. Macha is that layer: it connects through the live Macha–Front integration and runs on top of the Front shared inboxes you already use. It does not replace Front, your inboxes, or your teammates. If you want the wiring, connecting Front to Macha to route conversations to AI covers it, and building an AI agent for Front walks through a first agent end to end.

FAQ

How much does Front AI cost? As of capture, Front prices its heavier AI as add-ons on top of per-seat plans (Starter $25, Professional $65, Enterprise $105 per seat/mo annual). Autopilot starts at $0.05/conversation; Copilot and Smart QA are $20/seat/mo each (or included in Enterprise); Smart CSAT is $10/seat/mo. Compose, Summarize, Translate, and Topics are included on all plans. Always confirm current figures on front.com/pricing.

Is Front Autopilot billed per resolution or per conversation? Front's pricing page lists Autopilot as "starting at $0.05/conversation," i.e. a per-conversation model, as of capture. Third-party write-ups cite various per-resolution figures, but the authoritative per-conversation number is what appears on Front's own pricing page.

What happened to Front AI Answers? AI Answers is deprecated. Front's help center shows a banner stating it is no longer available for purchase and directs teams to Autopilot instead. Autopilot is the current AI agent product.

What does "per-action credits" mean and how is it different? Per-action pricing meters each step an AI agent takes — reading, tool-calling, drafting, sending — rather than charging per seat or per conversation. Macha uses credits consumed per AI action, never per resolution, so cost tracks the work done even when your automation rate varies.

Does adding Macha mean replacing Front AI? No. Macha is an AI agent layer that runs on top of the Front you already use via a live connector. Keep Front's Compose, Summarize, and Copilot where they help; layer Macha on for the multi-step, tool-calling work — the two coexist.

Want to see how per-action pricing maps to your real Front volume? Start a free trial of Macha and connect it to your Front in minutes.