How to Add an AI Chat Agent to Front Chat (2026)

What Front Chat is (and where AI plugs in)

Front Chat is Front's branded live-chat widget — the bubble you embed on a website or in a mobile app so visitors can start a conversation without leaving the page. Per Front's live chat product page, you can customize the widget with your own colors, logo, and header greeting, thread multiple conversations for the same contact, collect CSAT inside the chat, and send proactive messages for offers or updates. Native iOS and Android SDKs let you drop the same chat into a mobile app.

Because Front is a shared-inbox, collaborative platform, a Front Chat conversation lands in the same shared inbox as your email, SMS, and social channels. A support rep, a sales rep, or an ops teammate can all see it, comment internally, assign it, and reply — no context lost when the conversation moves between people or even between channels.

The important nuance is where AI actually plugs in. Front is explicit on its own page: "Front Chat is designed for real-time conversations through live chat and chatbots. To automate responses with AI, you should use Autopilot Resolve." In other words, the widget is the front door; the AI that answers behind it is Autopilot (Front's native option) — or a dedicated agent layer you connect on top.

What native Front Autopilot does well

Give Front credit here: Autopilot is a real AI agent, not a decision-tree bot, and for a lot of chat traffic it does the job. According to Front's Autopilot documentation, Autopilot auto-replies to conversations tagged with a Topic that has auto-replies enabled. When it fires, it "identifies any similar conversations and relevant knowledge articles to help generate the reply" — so it's grounded in your past resolutions and help center, not making things up freely.

A few native strengths worth naming honestly:

• It's built into the platform. No connector, no separate console — Autopilot lives inside Front's rules and Topics.
• It shows its work in the thread. When Autopilot is on a conversation you see "Autopilot is handling this conversation," and AI-sent replies are labeled "Generated by AI."
• Front's wider AI suite is strong. Copilot drafts and summarizes for agents, Smart QA scores conversation quality, and Smart CSAT reads sentiment — genuinely useful tools that make the human faster even when AI isn't sending the reply.

If your chat volume is mostly a handful of well-defined Topics with good help-center coverage, native Autopilot on the chat channel may be all you need.

Where native Front AI stops

Now the honest limits — the reasons teams add a dedicated agent layer on top rather than relying on Autopilot alone.

Autopilot needs the right Topic, cleanly. The docs are specific: the conversation must be tagged with a Topic that has auto-replies enabled, it must be in a shared inbox (not an individual one), and if a message spans multiple Topics, Autopilot won't reply at all. Real chat questions are messy — a visitor asks about a refund and a shipping delay in one line — and that multi-Topic case falls straight through to a human.

It's a paid add-on, billed per outcome. Front AI sits on top of the per-seat plans as an add-on. Per Front's pricing page, Autopilot starts at $0.05 per conversation, and Copilot is $20/seat/month (included on Enterprise). Some Autopilot Resolve tiers are quoted per resolution rather than per conversation. It's a fair model — but it's a separate line item layered on the seat cost, and it prices the outcome, not each thing the AI actually does.

And the old chat bot is gone. If you went looking for Front's classic chatbot, note that AI Answers is now legacy: Front's own help center states it "is no longer available for purchase" and points new buyers to Autopilot. So there's really one native path forward for automated chat answers, and it lives inside the Topic/rules model above.

None of this makes Autopilot bad. It makes it native and deterministic-adjacent: great inside its guardrails, quiet outside them. That "outside them" gap — the multi-Topic question, the one that needs a live order lookup, the answer that has to reason across two systems — is exactly where an AI agent layer earns its place.

Adding a resolving AI agent layer on top of Front

Macha is an AI agent layer that runs on top of the Front you already use through the live Macha–Front connector — it does not replace Front, your shared inboxes, your rules, or the Front Chat widget. You keep the widget, the branding, and the shared-inbox workflow exactly as they are. Macha adds the reasoning layer that reads a chat message, understands intent instead of matching a Topic tag, and resolves the question against a real source of truth.

Here's the practical playbook for wiring a resolving chat agent onto Front:

1. Keep Front Chat as your widget. The visitor experience, colors, greeting, and shared-inbox routing stay in Front. Nothing about the front door changes.
2. Connect Front to Macha. Link your Front account so incoming chat conversations can be read and answered by an agent. The mechanics are covered in connecting Front to Macha to route conversations to AI.
3. Ground the agent in your knowledge. Point the agent at your help center, docs, and past resolutions so every answer is grounded — the same grounding principle Autopilot uses, applied to a wider set of questions.
4. Give it tools for the questions a KB can't answer. A custom tool turns your REST API into something the agent can call — look up a live order, check subscription status, verify an invoice — so a chat about "did my refund go through?" gets a real answer, not a link.
5. Set the handoff rules. Decide exactly when the agent should stop and bring in a person (covered below), and what context it hands over.

Above: a Macha demo-org chat agent resolving a refund question, grounded in its connected knowledge base. This shows the Macha agent capability in the dashboard — not a live Front conversation — but it's exactly the resolution behavior you layer onto the Front Chat widget. For the broader picture, see Front AI explained and how to build an AI agent for Front.

The category this belongs to is AI agents for customer service: software that reads the conversation and does the reasoning-heavy part a keyword or Topic match structurally can't. Front stays the shared inbox and the widget; the agent becomes the resolver behind the chat bubble.

Handoff-to-teammate rules that don't drop the human

A resolving agent is only trustworthy if it knows when not to resolve. Both native Autopilot and a layered agent handle this — the difference is how much control you get.

Front's native behavior is clean and worth crediting: per the Autopilot docs, when Autopilot can't generate a reply, it passes the conversation to a teammate, who sees the handoff as a comment in the thread. That's a solid default — the human inherits the conversation with context attached.

A layered agent lets you make that handoff intentional rather than only a fallback. Good rules to set:

• Confidence floor. If the agent isn't confident it's grounded, it hands off instead of guessing — the same instinct as Autopilot's "can't generate a reply," but tunable.
• Topic and intent triggers. Route anything touching billing disputes, cancellations, security, or a named VIP straight to a person, no matter how confident the agent is.
• Explicit-ask trigger. If the visitor types "talk to a human," hand off immediately.
• Rich context on transfer. The teammate should inherit a summary, the sources the agent checked, and any tool results (the live order it looked up), so they're not re-reading a cold transcript.
• Business-hours awareness. Outside hours, the agent resolves what it can and captures the rest for the shared inbox to pick up — nobody left waiting on a bubble.

Because the conversation lives in Front's shared inbox the whole time, a support rep, sales rep, or ops teammate can jump in mid-chat, comment internally, or reassign — the handoff is a collaboration, not a wall.

Native Autopilot vs a layered agent, at a glance

The billing distinction is worth being precise about: Macha's credits are consumed per AI action — each search, each tool call, each reply the agent takes — not per resolution and not per seat. Automation and reasoning have different real costs, and it's honest to price the action rather than promise an outcome. For how the native side is priced, see Front pricing explained.

FAQ

Can I add an AI agent to the Front Chat widget? Yes. The widget stays Front Chat; the AI that answers behind it is either native Front Autopilot or a dedicated agent layer you connect on top. Front's own live-chat page says to use Autopilot Resolve to automate chat responses — and you can layer a resolving agent like Macha on top of the same widget without replacing it.

Does Front's native Autopilot work on chat? Autopilot auto-replies to conversations tagged with a Topic that has auto-replies enabled, in a shared inbox. It supports channels including email, SMS, WhatsApp, Slack, Portal, and Autopilot Resolve. If a message spans multiple Topics, or the inbox is individual rather than shared, it won't reply — those cases fall to a human.

What happened to Front AI Answers? AI Answers is now a legacy feature. Front's help center states it "is no longer available for purchase" and points teams to Autopilot instead. If you're setting up automated chat answers today, you're building on Autopilot — or a connected agent layer.

How does handoff-to-teammate work? Natively, when Autopilot can't generate a reply it passes the conversation to a teammate, who sees the handoff as a comment. A layered agent lets you go further — set confidence floors, Topic and VIP triggers, an explicit "talk to a human" trigger, and pass a full context summary so the teammate never inherits a cold transcript.

Does adding a Macha agent replace Front Chat? No. Macha runs on top of the Front you already use through the live connector. You keep the Front Chat widget, your shared inboxes, and your rules; Macha adds the agent that reads the chat, resolves the question against a grounded source of truth, and hands off to a teammate by your rules.

Ready to turn your Front Chat widget from a deflector into a resolver? Start a free trial of Macha and connect it to your Front in minutes.