Smart Routing in Front: AI Tagging, Teammate Assignment & @mention Comments

That gap is exactly what Macha's Front connector fills. Macha is not a replacement for Front — it's an AI agent layer that sits on top of the inbox you already run. When a conversation arrives, a Macha agent reads the whole thing (customer messages and internal comments), decides how it should be classified, applies the right tags, assigns the right teammate, and drops a private internal comment with an @mention so the person who gets it walks in with context instead of a cold subject line. We shipped the connector on June 23, 2026, alongside Gorgias.

This post walks through how that routing actually works — the tools the agent uses, the triggers that fire it, where it beats Front's built-in automation, and the honest cases where you should just use a Front rule instead.

Why "smart" routing, not just rules

Front's own automation is genuinely good at the mechanical part. A rule can watch an inbox, match on a keyword or sender or account, and fire an Assign to teammate action — including round-robin or load-balancing across a group so work spreads evenly (Front's routing docs). If your routing logic is "anything from @acme.com goes to Dana," a rule is the right tool and you don't need AI for it.

The friction shows up the moment routing depends on meaning. "Is this a billing question or a bug?" "Is this angry enough to escalate?" "Which of our six product areas does this touch?" Keyword rules approximate this and get it wrong on the edges — a customer who writes "I was charged but the app keeps crashing" trips both your billing rule and your bug rule, and neither one summarizes the situation for whoever opens it.

Front did ship an answer to this once — AI Tagging — but it's now legacy. Front's own help center states it's no longer available to new users, and even where it still runs it only works on email channels in shared inboxes, looks at subject and body only (it ignores the sender and the rest of the conversation context), caps you at 50 tags per inbox, allows one AI-tagging rule per inbox, and makes you hand-approve 10 example messages per tag to train it. It's a narrow, frozen classifier.

A Macha agent is the opposite of frozen. It reads the full conversation thread including prior internal comments, you describe the routing scheme in plain language (no per-tag training set), and the same agent that tags can also assign, comment, set a custom field, and draft a reply in one pass — because it has the whole Front toolset, not a single tagging action.

The toolset: what the agent can actually do in Front

When you connect Front (it authenticates with an API token under Connectors → Support), the agent gets 15 tools. For routing specifically, these are the ones that matter:

There's also Search Conversations, Search Contacts (look up a customer by email, phone, or social handle), Get Custom Fields, List Inboxes, Add Public Reply, and Read Attachment (it extracts text from PDF, DOCX, XLSX, CSV, and TXT files on the conversation) — so the same agent that routes can also look up history, read an attached invoice, and reply if you let it.

The important design point: Update Tags is non-destructive. This matters because routing agents run alongside humans and other rules. An agent adding a refund tag won't wipe the vip tag someone applied manually — it diffs and merges, the same reliable pattern we rebuilt for Zendesk tag updates earlier in June.

Triggers: when the routing agent fires

An agent only routes if something wakes it up. The Front connector ships four triggers:

• Conversation Created — fires when a brand-new conversation lands. This is the classic "triage on arrival" trigger.
• New Message Added — fires when an inbound reply lands on an existing conversation, so you can re-route when the topic shifts mid-thread.
• Conversation Assigned — fires when a conversation is assigned or reassigned, useful for "when this hits the escalations queue, summarize it."
• Custom Webhook — generates a URL you drop into any Front rule's Send a webhook action, so you control exactly which conversations call the agent.

That last one is the bridge between Front's rules and Macha's agents: let a Front rule do the cheap, deterministic filtering (only conversations in the Support inbox, only during business hours), then hand the survivors to the agent for the reasoning. You're not choosing between Front automation and Macha — you compose them.

A worked routing flow

Here's the shape of a triage-and-route agent on a Front shared inbox. The instruction you give it is plain English — something like "Read the conversation, classify it into one of our tag categories, set priority, assign it to the right teammate, and post an internal comment summarizing the issue and why you routed it there."

On a new conversation, the agent runs roughly this sequence:

1. Get Conversation — reads the full thread and any existing internal notes.
2. List Tags — loads your real tag scheme (e.g. billing, bug, shipping, vip).
3. Search Contacts (optional) — pulls the customer's identity/history if you want account-aware routing.
4. Update Tags — applies the classification, e.g. adds billing and urgent, leaves everything else intact.
5. List Teammates — finds who's available and who owns billing.
6. Assign Conversation — routes it to that teammate.
7. Add Internal Comment — posts: "@dana — billing dispute, customer charged twice on order #4821, wants a refund. Tagged billing/urgent. Full context above."

The teammate gets a notification with the summary already written. They open a conversation that's already classified, already prioritized, already assigned to them — and they know in one line why it's theirs. That's the difference between "smart" routing and a keyword rule: the rule moves the conversation; the agent moves it and explains it. This is conversation routing that reasons over meaning, not just the keywords you remembered to configure.

Macha ships built-in agent templates under Connectors → Support to start this off, so you're editing a working triage agent rather than building from a blank page.

What it costs to run

Macha is priced in credits per AI action, not per resolved conversation — so cost scales with how much the agent does, not with an opaque "resolution" meter. The default model, GPT-5.4 Mini, is 1 credit per response; if you want heavier reasoning on ambiguous tickets, GPT-5 is 2 credits (we dropped it from 3 on June 17). A lean triage agent that reads, tags, assigns, and comments is a handful of credits per conversation, and you choose the model per agent.

This is worth contrasting honestly with Front's native AI pricing. Front's AI add-ons — Copilot and Smart QA — sit on top of the per-seat plans (roughly +$20/seat/month each, per Hiver's pricing breakdown; approximate, not official), and Autopilot is billed around $0.89 per automatically resolved case. Those are useful features, but they're per-seat or per-resolution. Macha's credit model means a routing agent that touches 5,000 conversations costs the same whether you have 5 agents or 50 seats in Front. See the pricing page for current plans, and note the connector and agent builder live on the Professional tier and up.

Watch-outs: when to use a Front rule instead

This is an agent layer, not a magic wand. Be deliberate about where it earns its keep.

• Deterministic routing belongs in Front. If the rule is "from @acme.com → assign to the account owner," a native Front rule is faster, free, and won't ever mis-classify. Don't spend credits on a decision a keyword already makes correctly.
• Round-robin / load-balancing is Front's job. Front rules can distribute across a group evenly. A Macha agent assigns to a reasoned teammate ("who handles billing"), not to balance load — pick the tool that matches your goal, or compose them.
• Models can mis-tag the edge cases. A genuinely ambiguous conversation can land the wrong tag. Keep a human-review view for anything the agent marks low-confidence, and use the internal comment to make the agent show its reasoning so a human can sanity-check the routing at a glance.
• Don't let two systems fight. If a Front AI-tagging rule (where still active) and a Macha agent both tag the same inbox, you'll get noise. Pick one classifier per inbox. Because Macha reads the full thread and your real tag list, it's usually the one to keep.
• Public replies need a tighter leash than routing. Tagging and assigning are low-risk and reversible; auto-sending a public reply is not. Many teams run the routing agent autonomously and keep replies as drafts for human approval at first.

Where this fits with the rest of Macha

Routing in Front is one expression of a pattern Macha runs across every helpdesk it connects — the same triage-and-route capability exists on Zendesk, Freshdesk, and Gorgias, because the agent logic is helpdesk-agnostic and only the tools change. If you already run agents on Zendesk, the Front connector is the same builder pointed at a shared inbox. You can read the full tool reference on the Front integration page and the setup steps in the docs.

FAQ

Does Macha replace Front? No. Macha is an AI agent layer that runs on top of Front. Front stays your inbox, your channels, and your system of record; Macha reads conversations and takes actions (tag, assign, comment, reply) through Front's API.

How does Macha route a conversation to the right teammate? The agent uses List Teammates and List Teams to see who's available and what they own, reasons over the conversation, then calls Assign Conversation to assign it — and typically posts an @mention internal comment so that teammate gets notified with context.

Is this the same as Front's AI Tagging? No. Front's native AI Tagging is a legacy feature (no longer available to new users), email-only, looks at subject and body only, and needs per-tag training. A Macha agent reads the full thread including internal comments, uses your real tag scheme via List Tags, and the same agent can also assign, comment, and set fields in one run.

Will the agent overwrite tags a human already applied? No. Update Tags diffs against the current tag set — it adds and removes only what changed and preserves the rest.

What triggers an agent in Front? Four triggers: Conversation Created, New Message Added, Conversation Assigned, and a Custom Webhook you can call from any Front rule.

Can the agent reply to the customer, or only route internally? It can do both. Add Public Reply sends a customer-facing reply; many teams start with routing-only (tag + assign + internal comment) and keep public replies as human-approved drafts.

How much does it cost? Credits per AI action — default GPT-5.4 Mini is 1 credit per response — not per resolution. See the pricing page for plans. Start with a 7-day free trial, no credit card required.

Try it

If your Front inbox routes by keyword today and your team still opens cold conversations, a routing agent is a fast win. Start a 7-day free trial, no credit card required, connect Front under Connectors → Support, and adapt the built-in triage template to your tag scheme — or read the Front integration details first.

Written by Abbas (Customer Support & AI, Macha) · Reviewed by Ankeet Guha (Co-founder & CTO) · Published 2026-06-24 · Last updated 2026-06-24.