Mike HeapMike is an experienced Product Manager who focuses on all the “non-development” areas of My AskAI, from finance and customer success to product design, copywriting, testing and more.
Table of Contents
- What is Front AI?
- How easy is it to set up Front AI?
- What channels does Front AI work in?
- What are the limitations of Front AI?
- What knowledge sources can I train Front AI on?
- What features does Front AI have?
- How do I improve Front AI responses?
- What resolution rate can I expect from Front AI?
- What AI model does Front AI use?
- What languages does Front AI work in?
- How secure is Front?
- Who is using Front AI?
- How much does Front AI cost?
- Does Front AI have a free trial?
- Is Front AI worth it?
- What are the Pros and Cons of Front AI?
- Pros
- Cons
- FAQs
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Front says Autopilot can "resolve up to 70% of requests." It's also never published a resolution rate, only officially supports English, and gates the real Autopilot price behind a sales call. Here's the full breakdown.
Front markets its AI with a simple promise: Autopilot can "resolve up to 70% of requests". It's a good line. It's also the one number Front has never actually published, and once you go looking, I keep finding a few other gaps too.
I've spent the last few years on calls with support leaders weighing exactly this decision, so I know the questions that actually get asked. Most people land here in one of three spots:
- You're already on Front and deciding whether to switch on Copilot or Autopilot, and what it'll really cost once the add-ons stack up.
- You're shopping helpdesks and weighing Front's AI against Intercom Fin, Zendesk AI, or an agent that plugs into whatever you already run.
- You're trying to model the cost of Autopilot and hitting a "Talk to Sales" button where the real number should be.
This guide breaks down what Front AI is, how it works, the channels and languages it covers, its real limitations, what it costs, the resolution rate you can actually expect, and who it's right (and wrong) for. Let's get into it.
What is Front AI?
TL;DR: Front AI is the AI layer inside Front's shared-inbox helpdesk, split into three loops: Automate (the Autopilot agent), Assist (Copilot, Compose, Summarize, Translate), and Analyze (Topics, Smart QA, Smart CSAT). It's assistive-first, with a newer autonomous agent in Autopilot.
Front is a customer-communication platform built around a shared inbox. Email, chat, SMS, WhatsApp, Slack and social all land in one collaborative workspace that sits somewhere between a team mailbox and a full help desk. It was founded in 2013 by Mathilde Collin and Laurent Perrin, has raised around $204M, and says it now serves 9,000+ customers at $100M+ ARR.
"Front AI" is the umbrella brand for everything AI inside that platform, organized around three loops. Automate is Autopilot, Front's autonomous agent, plus Playbooks (multi-step workflows) and Resolve (in-app self-service).
Assist is the agent-productivity layer: Copilot for suggested replies, Compose for drafting, Summarize and Translate. Analyze is Topics (AI clustering of conversations), Smart QA (auto-scored quality) and Smart CSAT (satisfaction scoring without a survey).
The one-line version: Front AI is assistive-first. The productivity tools (Copilot, Summarize, Smart QA) are mature and genuinely useful. Autopilot, the agent that resolves tickets on its own, is newer and more cautious by design.
Front's rollout tells that story. AI Compose and Summarize shipped in March 2023, the "Front AI" brand was unified in July 2025, and Autopilot only reached general availability, with Playbooks and Resolve, in late 2025 into 2026. Front also acquired Idiomatic in November 2024, a voice-of-customer analytics company (not a voice/telephony one, which trips a few people up), and there's no first-party Front voice agent.
Its own users rate the platform highly. Front holds a 4.7/5 across 2,407 reviews on G2, mostly from small-business and mid-market teams.
G2: Front scores 4.7/5 from 2,407 reviews on G2, strong for the platform overall, though AI-specific feedback runs more mixed. One reviewer notes "the AI chatbot says it's applying rules but doesn't actually do so."
My AskAI works differently: instead of an AI tied to one inbox, it's an AI agent that plugs into the helpdesk you already run (Zendesk, Intercom, Freshdesk, Gorgias or HubSpot). You keep your stack; the AI layers on top.
How easy is it to set up Front AI?
TL;DR: Setup is no-code but not a single toggle. You must be on a paid plan, build Topics first (Front scans up to 10,000 recent conversations, ~1-2 hours), connect knowledge, review sample replies, then switch on auto-replies one Topic at a time. There's a ~24-hour warm-up.
Setting up Front AI is admin-driven, and only company or workspace admins can enable it. The documented Autopilot setup flow runs roughly like this:
- Build Topics first. Front AI scans up to 10,000 conversations from the past 30 days and auto-suggests Topics; you review, rename and merge duplicates. Front puts Topic accuracy at around 85%.
- Enable Autopilot in workspace settings and pick which shared inboxes it runs on.
- Connect a knowledge source (the Front knowledge base, a public URL, or Notion/Google Drive/SharePoint).
- Review the "Ready for auto-replies" Topics, compare the AI's sample drafts against real teammate replies, and switch auto-replies on one Topic at a time.
- Set the AI disclosure text appended to every AI reply.
Two constraints matter here. Autopilot and Copilot only run on shared inboxes, so anyone working out of an individual inbox is out of scope.
There's also a warm-up. Reviewers report the AI takes roughly a day after you connect knowledge before its answers get genuinely useful, and word-on-the-street is that the real setup work (cleaning Topics, writing rules) is heavier than a one-click toggle implies.
For comparison, we built My AskAI to go live inside your existing helpdesk in about ten minutes, with the bulk of the effort in month one and upkeep of roughly 30 minutes a week. Your macros, tags and routing stay exactly as they are.
What channels does Front AI work in?
TL;DR: Front the platform is fully omnichannel, but AI coverage is uneven. Autopilot is the most complete (email, chat, SMS, WhatsApp, Slack); Copilot covers most of those; AI on Meta social looks limited; and there's no first-party voice agent (voice runs through Dialpad/Aircall/RingCentral).
At the platform level Front is genuinely omnichannel: email, Front Chat, SMS, WhatsApp, Slack, Facebook, Instagram, and voice through integrations. The AI coverage across those channels is where it gets uneven (and easy to miss on a feature list).
Autopilot is the most complete, working across email, chat, SMS, WhatsApp, Slack (including Slack Connect) and custom channels. Copilot covers email, chat, portal, Slack, SMS and WhatsApp, and Compose's "Generate" is email-only. Front's Copilot and Smart CSAT help articles don't list Facebook or Instagram as supported, which suggests AI features are limited on Meta's social channels even though those channels exist as inboxes.
Voice is the clearest gap. Front integrates with Dialpad, Aircall and RingCentral, and partners provide call summaries, but there's no first-party Front voice AI agent. If native voice deflection is on your roadmap, Front won't do it for you.
My AskAI answers in whatever channels your helpdesk routes to it, social conversations included when they flow through Gorgias, Zendesk or the like. Like Front, we don't offer a native voice agent today.
What are the limitations of Front AI?
TL;DR: Eight to weigh: you can't buy the AI standalone, a ~3,000-page knowledge cap, officially English-only AI, a sales-gated Autopilot price with stacked per-seat add-ons, no simulation sandbox, a black box you can't directly correct, shared-inboxes-only, and lukewarm reviewer sentiment on the AI specifically.
This is the section that decides things, so I'll be specific. There are eight limitations I'd weigh before committing.
- You can't buy it standalone. Front AI only exists inside Front, so adopting it means moving your support onto Front. If your team already lives in Zendesk, Intercom or Jira, that's a full platform migration to take on.
- Knowledge sources are capped. Front crawls up to ~3,000 pages from a public website, re-syncs manually at most once every 24 hours, and can't reach password-protected internal wikis. There's no dedicated way to upload arbitrary files, so third-party content comes through the Notion, Google Drive or SharePoint connectors.
- The AI is officially English-only. Front is direct about it: "Only English is officially supported at this time. While it is possible to use this feature with other languages, unexpected results may occur." That covers Autopilot, Copilot, Summarize, Topics and knowledge sources.
- The real Autopilot price still needs a sales call. Front's pricing page now shows Autopilot "starting at $0.05/conversation", an improvement on the old "contact us," but that's a floor and it routes to "Talk to Sales" for anything real. The assistive AI also stacks per seat on top: Copilot at $20, Smart QA at $20, Smart CSAT at $10.
- There's no simulation or sandbox. You can't replay past tickets to forecast how the AI would have handled them before go-live. Front AI has to be switched on directly against live customer conversations, which is a real evaluation risk if you've been burned by an AI rollout before.
- It's a black box you can't correct. Front says outright that it "does not train any models" itself, and that discarding a bad answer doesn't train the AI. Improvements come only from updated knowledge and the messages your team sends, so there's no direct "teach it the right answer" lever.
- Shared inboxes only. Copilot and Autopilot don't run in individual inboxes, so anyone whose work happens in a personal inbox is outside the AI's reach.
- Reviewers are lukewarm on the AI specifically. A Capterra reviewer sums up a common note: "AI features are pretty limited right now." The platform scores well; the AI layer draws more caveats.
Most of these have a direct counter in the overlay model. My AskAI keeps your helpdesk in place, takes direct PDF and DOCX uploads alongside connectors for Google Drive, Notion, Confluence and more, works in 95 languages, and lets you test it in an internal-notes mode side-by-side with your current setup before a customer sees anything. And where Front is a black box, our team can ask Echo why the agent gave any answer and which source it used.
What knowledge sources can I train Front AI on?
TL;DR: Four types: the Front knowledge base (best), a public website (~3,000-page cap), Notion/Google Drive/SharePoint connectors, and always-on learning from past conversations. Plus Notes, attachment reading and fact-invalidation. There's no dedicated arbitrary file-upload source.
Front says its AI features are "only as powerful as the information they can access". I read that as the polite version of "garbage in, garbage out." Front supports four main knowledge types:
- The Front knowledge base, its recommended "most reliable source," with updates flowing into the AI within minutes.
- A public website or external URL, crawled up to the ~3,000-page cap, with manual re-sync and no support for protected sites.
- Third-party connectors: Notion, Google Drive and Microsoft SharePoint.
- Historical conversations, always on, so Front learns tone and common resolutions from past tickets.
There are supporting pieces too: admin-written Notes to patch gaps, attachment reading for PDFs and images, and fact-invalidation to trash a specific fact so it stops being used. What's missing is a dedicated file-upload type and any per-agent knowledge scoping, since sources are configured per workspace.
One thing to flag for anyone earlier in their AI journey: Front's model assumes you already have a solid knowledge base to point it at. If you don't, you're stuck at the starting line.
We cover more sources out of the box: Google Drive, Notion, Confluence, SharePoint, OneDrive, Dropbox, Salesforce, Shopify, your helpdesk help center, plus direct PDF and DOCX uploads. And for teams with no written docs at all, training on historic tickets auto-drafts starter articles from your past resolved tickets (5,000 by default) so you can get going from scratch.
What features does Front AI have?
TL;DR: Three layers: Autopilot (the autonomous agent, plus Playbooks and Resolve), the assist layer (Copilot, Compose, Summarize, Translate), and the analyze layer (Topics, Smart QA, Smart CSAT). The old AI Answers and AI Tagging products are legacy, and Front runs a single tenant-level agent.
Front AI breaks into three layers, and here's what each one actually does (I'll skip the marketing gloss).
- Autopilot, the AI agent. Front's headline agent auto-resolves conversations on the Topics you enable, drawing on past conversations and connected knowledge, and hands off to a teammate when it can't answer. It supports mid-conversation "step-in," matches your team's tone, and reads PDF and image attachments. Autopilot Playbooks extend it into plain-language multi-step workflows, and Autopilot Resolve embeds self-service inside your own app or website.
- Copilot, Compose, Summarize, Translate, the assist layer. Copilot suggests replies drawn from similar past conversations (Front reports one beta customer, Fathom, used over 65% of the suggestions). Compose drafts and adjusts tone, and translates into 15 languages, rate-limited to 200 requests per user per day. Summarize auto-generates a conversation summary once there are four or more messages (and keeps updating it as the thread grows).
- Topics, Smart QA, Smart CSAT, the analyze layer. Topics cluster conversations for both reporting and Autopilot routing. Smart QA auto-scores every closed ticket against up to 15 custom criteria, and Smart CSAT infers satisfaction on every meaningful conversation without a survey.
Two things are worth knowing (both easy to miss on the marketing pages). The older AI Answers and AI Tagging products are legacy, deprecated in favor of Autopilot and Topics.
Front also runs a single tenant-level agent shaped by Topics and rules, where some competitors market a set of separate bots. Tone-matching is automatic, and Front is explicit that you "cannot explicitly train Copilot or Autopilot to sound like you" beyond that.
Our own agentic layer is Tasks and Tools: natural-language, multi-step workflows (refunds, order lookups, account changes) that you can run fully autonomously or as propose-then-approve, whichever you're comfortable with. Under the hood we use a mix of OpenAI, Google and Anthropic models, picked per task.
How do I improve Front AI responses?
TL;DR: Through supervised curation: cleaner Topics, fresher knowledge, and fact-invalidation to drop bad facts, plus selective auto-replies and Smart QA. Front trains no models itself, so there's no fine-tuning or labeled-feedback loop.
Front's improvement model is supervised curation. The levers are keeping Topics clean (merge duplicates, review the similarity score before auto-enabling), keeping connected knowledge fresh, using fact-invalidation to remove bad facts, enabling auto-replies selectively Topic by Topic, and leaning on Smart QA as a feedback signal.
What you won't find is a fine-tuning pipeline or a labeled-feedback loop. Front works through model vendors rather than training anything itself, so "improving" the AI really comes down to better Topics and better knowledge.
This is one place the overlay model differs. Our Self-Learning feature automatically drafts new knowledge articles by comparing the AI's reply to the human agent's actual reply on handed-over tickets, so the knowledge base closes its own gaps over time instead of waiting for someone to notice them.
What resolution rate can I expect from Front AI?
TL;DR: Front has never published a headline resolution or deflection rate. It defines a "resolution" as a billing event (an AI reply with no follow-up within 24-72 hours), and its case studies lead on hours saved rather than tickets deflected. The wider field clusters around a 70% median.
Here's the part I always flag: Front has never published a headline resolution or deflection rate. Intercom claims Fin resolves around 56-62% of queries; Decagon, Ada and Fini routinely cite 70-80%. Front's marketing instead argues that "deflection is cheap, churn isn't", and that chasing a high deflection number is the wrong goal.
The closest Front comes to a number is operational. A "resolution" is a billing event: an AI reply followed by no customer follow-up within 24 to 72 hours (so a wrong answer the customer simply gives up on still counts). That's a billing definition, and accuracy never comes into it.
Its case studies lean on time saved instead: Branch Insurance reports 482% ROI and 75% faster responses after switching from Zendesk, Boundless Immigration saved 10,000+ hours a quarter, and Reed & Mackay hit 97% CSAT.
For context on where that leaves Front, our own 2026 vendor scorecard put Front in the 41-56% band, against 84% for My AskAI and 74% for eesel. Across the wider field, industry resolution rates cluster around a median of 70%, though I'd treat that as a directional aggregate (every vendor defines resolution differently, and the label alone can move the number by more than ten points).
So Front AI today is more assistive than autonomous. If you need a defensible "X% of tickets handled fully by AI" figure for a board, Front can't give you one.
Front frames that as responsible restraint, and I'd push back gently: my own view is that near-total automation is achievable and better for customers when the AI has the right access and a system that flags what it struggles with. Not publishing a number is a choice, and buyers who want a measurable one have options.
When we quote our own resolution rate, it's 72% on a rolling 30-day basis across the full customer base. We count a conversation as resolved when the AI handled it without escalating to a human, with escalation made deliberately easy, rather than claiming to know an issue was truly solved.
What AI model does Front AI use?
TL;DR: OpenAI and Azure OpenAI GPT models, plus Mistral hosted on AWS. No Anthropic, and Front doesn't disclose specific GPT versions. Front trains no foundation models itself and applies zero data retention at the API layer.
Front is specific here. Its AI features FAQ names the providers directly: OpenAI and Azure OpenAI's GPT models, plus Mistral models hosted on Amazon AWS.
There's no Anthropic in the mix, and Front doesn't disclose specific GPT versions. Front accesses these through vendor APIs, trains no foundation models itself, applies zero data retention at the API layer, and confirms customer data isn't used to train the vendors' models.
For what it's worth, "what model do you use?" is a question I'd gently push back on for any AI agent. A real agent fires ten or more orchestrated model calls between question and answer (one to summarize the conversation, one to detect language, one to apply guidance and tone, one to decide whether a workflow should run), each tuned for a different job.
We use a mix of OpenAI, Google and Anthropic models depending on the task and A/B test them continuously. A vendor that can answer "what model?" in one word is usually telling you the setup is simpler than it should be.
What languages does Front AI work in?
TL;DR: Officially English only, for nearly every AI feature. Autopilot, Copilot, Summarize and Topics all state English is the only supported language; other languages are "unsupported" and unpredictable. Translate is the one exception.
I went through each AI feature's help doc, and the answer comes back the same: officially English only. Front repeats the line across Autopilot, Copilot, Summarize and Topics: only English is officially supported, and while the underlying vendor models handle 40+ languages, results outside English are unsupported. Topics can interpret conversations in other languages but generate the Topics themselves in English.
The exception is Translate, which auto-detects and translates across email and chat channels. Translation still isn't the same as an agent that natively understands and answers in the customer's language, and for that, Front's own documentation sets the ceiling at English.
If multilingual support matters, it's the sharpest contrast in this whole guide. We built our agent to work in 95 languages, auto-detected per message, replying in the customer's language by default.
How secure is Front?
TL;DR: Very. Front holds SOC 2 Type II, ISO 27001, GDPR, CCPA and HIPAA (with a BAA), offers US/EU residency, and applies zero data retention at the AI model layer. It's among the strongest platforms in this category on compliance.
Security is one of Front's genuine strengths. I'd put it among the most mature platforms in this category. Front holds SOC 2 Type II, ISO 27001, GDPR, CCPA and HIPAA compliance (HIPAA with a signed BAA), offers US or EU data residency, and encrypts data with AES-256 at rest and TLS 1.2 in transit.
It runs SAML SSO, 2FA, IP allowlisting, annual penetration tests and a HackerOne bug bounty, and applies zero data retention at the AI model layer. If your security review is strict, Front will pass it comfortably.
On our side, My AskAI is SOC 2 Type II certified and GDPR compliant, with a live trust report your security team can work through.
Who is using Front AI?
TL;DR: 9,000+ customers, skewing SMB and mid-market. AI-named customers cluster in logistics, travel, immigration, insurance and B2B SaaS: Boundless Immigration, Uber Freight, BentoBox, Central Storage & Warehouse, Reed & Mackay and Branch Insurance.
Front says it has 9,000+ customers, and its review base skews small-business and mid-market, with a thinner slice of enterprise. The customers it spotlights specifically for AI usage sit in a clear set of verticals: logistics, travel, immigration, insurance and B2B SaaS.
- Boundless Immigration: Autopilot, Topics and Copilot; 10,000+ hours saved per quarter.
- Uber Freight: organic adoption of AI Summarize across a large logistics operation.
- BentoBox: knowledge base plus Copilot, with a 50% improvement in handling time.
- Central Storage & Warehouse: Autopilot Playbooks cut scheduling time by 90%.
- Reed & Mackay: 97% CSAT and a 43% productivity gain.
- Branch Insurance: 482% ROI after switching from Zendesk.
One pattern I'd point out: even on Front's own customer page, most testimonials lead with collaboration, routing or Copilot summaries over Autopilot autonomously resolving tickets. Boundless, the headline Autopilot reference, still frames it as AI surfacing answers under human control.
For context on our side, 200+ ecommerce and SaaS businesses run AI support with us, our agents have resolved over 1,000,000 tickets, and we hold a rolling 72% resolution rate across the base. In the B2B SaaS space Front plays in, RecruitCRM reached 68% AI resolution and TravelJoy hit 80%, both inside their existing helpdesk.
How much does Front AI cost?
TL;DR: Hybrid pricing. Base seats run $25/$65/$105 per month; Copilot and Smart QA are $20/seat each and Smart CSAT $10/seat (all included on Enterprise); Autopilot starts at $0.05/conversation with the real rate behind "Talk to Sales." The full AI suite on Professional costs more than the Enterprise base.
Front's pricing is hybrid: per-seat for the platform and assistive AI, per-conversation for the autonomous agent. The base plans (billed annually) are:
- Starter, $25/seat/mo (up to 10 seats): Topics, Compose, Translate and Summarize included; Copilot, Smart QA and Smart CSAT are paid add-ons.
- Professional, $65/seat/mo (up to 50 seats): same AI inclusions, plus omnichannel, more rules and SSO/SCIM.
- Enterprise, $105/seat/mo: Copilot, Smart QA and Smart CSAT included; Autopilot still an add-on.
The AI add-ons stack on top: Copilot $20/seat/mo, Smart QA $20/seat/mo, Smart CSAT $10/seat/mo (the last two bundle at $25), and Autopilot from $0.05/conversation with the real rate behind "Talk to Sales."
Two things catch people out. The add-ons compound: a 10-seat Professional team adding Copilot and Smart QA pays 10 × ($65 + $20 + $20) = $1,050/mo, a 61% premium over the $650 base. And the full AI suite on Professional works out to $115/seat, more than the Enterprise base of $105.
Because Autopilot is priced per conversation and gated behind sales, you also can't fully model your bill from the page. Here's an illustrative monthly cost I'd sketch for a 20-agent team on Professional handling 10,000 conversations:
Assumption | Value |
Conversations per month | 10,000 |
Human agents | 20 |
Base plan | Professional, $65/seat |
Copilot add-on | $20/seat |
Autopilot | from $0.05/conversation (Talk to Sales) |
Twenty seats on Professional with Copilot runs 20 × $85 = $1,700/mo. Autopilot handling all 10,000 conversations at the $0.05 floor adds roughly $500/mo. So the illustrative total is around $2,200/mo, before you add Smart QA or Smart CSAT.
Our pricing is flat and published: $0.10 per ticket (every two AI replies is one credit), so 10,000 tickets runs to roughly $1,000 in usage, and a typical Scale plan at real volume lands near $1,299/mo, against Intercom Fin near $7,425 for the same load. Because the natural question at any price line is "can I test it first," our trial is 30 days, all features unlocked, unlimited tickets, no card.
Does Front AI have a free trial?
TL;DR: Yes, a 14-day trial with no credit card, mirroring the Professional plan. The catch: it excludes full Copilot, Smart QA, Smart CSAT and Autopilot, so you can't self-serve trial Front's flagship AI agent. To pilot Autopilot, you go through sales.
Yes. Front offers a 14-day trial with no credit card required, and it mirrors the Professional plan. There's a real catch for AI evaluation, though: the trial includes Topics, Compose, Translate, Summarize and a throttled Copilot, but leaves out full Copilot, Smart QA, Smart CSAT and Autopilot.
So you can't self-serve trial Front's flagship AI agent. To pilot Autopilot, you go through sales, and there's no free tier either (the lowest paid entry is Starter at $25/seat).
That's a real difference from how we run trials: 30 days, every feature unlocked including the AI agent, unlimited tickets, no card, plus an internal-notes mode so you can run the agent silently alongside your current setup and see how it would have answered before anything reaches a customer.
Is Front AI worth it?
TL;DR: If you're already on Front and want assistive AI with a human in the loop, yes: start with Copilot before Autopilot. If you're shopping greenfield for autonomous AI, support more than one language, or are scaling cost-sensitively, look wider first.
It depends entirely on where you're starting from.
Front AI is worth turning on if you're already on Front and you want assistive AI (Copilot suggestions, Summarize, Smart QA) with a human firmly in the loop. The sensible path is to start with Copilot before paying for Autopilot. Front's control-first philosophy genuinely fits high-stakes B2B work in immigration, freight and financial services, where blindly deflecting tickets is the bigger risk.
It's a weaker buy if you're shopping greenfield for best-in-class autonomous AI, if you support customers in more than one language, if you're cost-sensitive and scaling fast, or if you're running high-volume ecommerce support where deflection economics dominate. In those cases the assistive-first design, the English-only ceiling and the stacked add-on pricing all work against you.
Here's how Front and My AskAI stack up at a glance:
Criteria | Front AI | My AskAI |
Deployment | Move onto Front's inbox | Overlays your existing helpdesk |
Languages (AI) | Officially English only | 95 languages |
Pricing model | Per-seat + per-conversation, sales-gated | Flat $0.10/ticket, published |
Test before live | No sandbox; trial excludes Autopilot | Internal-notes side-by-side, 30-day full trial |
Published resolution rate | None | 72% rolling |
Security | SOC 2 Type II, ISO 27001, HIPAA-BAA | SOC 2 Type II, GDPR |
Choose Front AI if…
- You're already on Front and want assistive AI (Copilot, Summarize, Smart QA) without leaving your inbox.
- Your support is high-stakes B2B (immigration, freight, finance) where human-in-the-loop control beats aggressive deflection.
- You need ISO 27001 or a HIPAA BAA and want AI and helpdesk from one mature vendor.
- Your team works in English and lives in shared inboxes.
Don't choose Front AI if…
- You want to keep your existing helpdesk (Zendesk, Intercom, Freshdesk, Gorgias, HubSpot) instead of migrating onto Front.
- You support customers in more than one language.
- You want to test an AI agent on past tickets before going live, or self-serve a full trial.
- You need a defensible, published resolution rate and flat, predictable pricing.
What are the Pros and Cons of Front AI?
Pros
- A genuinely good shared inbox with useful assistive AI: Copilot, Summarize and Smart QA are mature and land well for agent productivity.
- A control-first design that suits high-stakes B2B: for immigration, freight and finance, the human-in-the-loop default is a feature.
- Strong, mature security: SOC 2 Type II, ISO 27001, HIPAA with a BAA, and US/EU residency put Front among the best in the category on compliance.
Cons
- No published resolution rate and an assistive-first agent: Front leans on hours-saved case studies rather than a deflection number (see the resolution-rate section).
- Officially English-only AI: a hard ceiling for any multilingual support team (see the languages section).
- Autopilot's real price is still sales-gated, and the add-ons stack: the $0.05/conversation floor plus per-seat Copilot, Smart QA and Smart CSAT make the true cost hard to model (see the pricing section).
- No simulation sandbox: you enable the AI on live conversations, and the trial excludes Autopilot (see the limitations and free-trial sections).
Front AI
- Brand: Front
- Rating: 7/10
- In a sentence: A best-in-class shared inbox with competent, control-first assistive AI, but not yet a top-tier autonomous agent, and priced and language-limited in ways greenfield AI-first buyers will feel.
If you want a wider view of the field and how My AskAI compares, our Front alternatives and vendor comparison is worth a read alongside this guide.
FAQs
What is Front AI?
Front AI is the suite of AI features built into Front's shared-inbox helpdesk, grouped as Automate (the Autopilot agent), Assist (Copilot, Compose, Summarize, Translate) and Analyze (Topics, Smart QA, Smart CSAT). In our reading it's assistive-first: strong on agent productivity, more cautious on fully autonomous resolution.
What's the difference between Front Copilot and Autopilot?
Copilot is the agent-assist layer: it drafts suggested replies for a human to review and send. Autopilot is the autonomous agent: it replies to customers directly on the Topics you enable and hands off to a human when it can't answer. Copilot is priced per seat; Autopilot is priced per conversation.
How much does Front AI cost?
Front's base plans run $25, $65 and $105 per seat per month. The AI stacks on top: Copilot and Smart QA are $20/seat each and Smart CSAT is $10/seat (all included on Enterprise), and Autopilot starts at $0.05/conversation with the real rate behind a sales call. A 10-seat Professional team with Copilot and Smart QA pays around $1,050/mo before Autopilot usage.
How do I turn on Front AI?
An admin builds Topics first (Front scans up to 10,000 recent conversations), then enables Autopilot on chosen shared inboxes, connects a knowledge source, reviews the AI's sample replies against real teammate replies, and switches auto-replies on one Topic at a time. Copilot and Autopilot only work in shared inboxes.
What resolution rate does Front AI achieve?
Front doesn't publish one. Front defines a "resolution" as a billing event (an AI reply with no customer follow-up within 24 to 72 hours) and its case studies emphasize hours saved over deflection percentage. For context, we've seen the wider field cluster around a 70% median, but Front hasn't put a comparable number on the record.
Does Front AI support languages other than English?
Officially, no. Front states that only English is supported for Autopilot, Copilot, Summarize and Topics, with other languages unsupported and unpredictable. Its Translate feature is the exception. For genuinely multilingual AI support, we built our own agent to work in 95 languages out of the box.
What knowledge sources can Front AI use?
Front's own knowledge base, a public website (capped at ~3,000 pages), and Notion, Google Drive and SharePoint connectors, plus always-on learning from historical conversations. There's no dedicated arbitrary file-upload knowledge type.
Can I test Front AI before going live?
Only partially. There's no simulation or sandbox to replay past tickets, and the 14-day trial excludes Autopilot, so you can't fully evaluate the agent without enabling it on live conversations or going through sales. This is one reason we built an internal-notes mode into My AskAI, so you can run the agent silently against real tickets before any customer sees a reply.
Is Front AI secure?
Yes. Front is mature on security, with SOC 2 Type II, ISO 27001, GDPR, CCPA and HIPAA (with a BAA), US/EU data residency, SSO, and zero data retention at the AI model layer. It's one of the strongest platforms in this category on compliance.
Does Front AI work in individual inboxes?
No. Copilot and Autopilot only operate on shared inboxes, so support handled out of a personal inbox is outside the AI's reach.
What AI models does Front use?
Front uses OpenAI and Azure OpenAI's GPT models plus Mistral models hosted on AWS. Front doesn't use Anthropic models and doesn't disclose specific GPT versions, trains no foundation models itself, and applies zero data retention at the API layer.
Who uses Front AI?
Front highlights AI usage from customers like Boundless Immigration (10,000+ hours saved per quarter), Uber Freight, BentoBox, Central Storage & Warehouse, Reed & Mackay and Branch Insurance, concentrated in logistics, travel, immigration, insurance and B2B SaaS.
What are the best alternatives to Front AI?
If you want an AI agent that overlays your existing helpdesk instead of requiring a move onto Front, with transparent per-ticket pricing, multilingual support and a proper testing mode, that's the category My AskAI sits in. Our Front alternatives and vendor comparison breaks down the field.
