If your support volume is genuinely small (under a few hundred tickets a month), you probably don’t need any of these. A well-organized help center, a shared inbox, and a templated reply library will get you further than a $30,000-a-year contract. The reason to deploy an AI customer support agent is that your team is missing nights and weekends, that ticket volume is growing faster than headcount, or that “where is my order” and password-reset traffic are eating real agent hours. We tested for that team.
Who this is for
This guide is for support and CX leaders evaluating an AI agent in 2026: ecommerce brands drowning in WISMO tickets, SaaS teams whose product questions repeat themselves, and ops leaders at mid-market and enterprise companies who’ve been told to “implement AI” and asked for the resolution rate in a quarter. If you’re a small DTC brand under 500 tickets/month, skip to Lyro. If your support stack is already Zendesk, read the runner-up section before anything else. If you’re an enterprise with 300,000+ annual conversations and a procurement process, the relevant question is Ada vs. Decagon vs. Fin, and we cover that below.
Fin wins this guide because it does the boring thing well. It publishes its price, it works with the helpdesk you already have, and it tells the truth about resolution rates in its own case studies.
All Intercom plans include access to Fin, and pricing is simple: $0.99 per outcome.
A billable outcome is a resolution (no further help requested after Fin’s last answer), a procedure handoff (Fin completes a configured workflow ending in handoff to a human), a disqualification, or a qualification.
Fin is sold two ways. You can run it standalone on top of an existing helpdesk, or you can pair it with Intercom’s own helpdesk for the deepest integration.
There are no integration fees, no setup fees, and no platform charges when using Fin with an existing helpdesk like Zendesk, Salesforce, or HubSpot. Unlimited teammates are included at no extra cost. For teams that want the deepest integration, Fin also works with Intercom’s Helpdesk starting at $29/seat/month on top of the per-outcome fee. But this is optional. The core product is Fin at $0.99/outcome.
That last sentence is what separates Fin from Ada and Decagon, both of which are essentially line items you bolt onto a helpdesk you still have to pay for separately.
The honest part of the pitch is the resolution number.
Fin’s average resolution rate is 76% across 8,000+ customers, improving approximately 1% every month.
The more interesting number is the one in the case studies.
Real customer-reported resolution rates from Intercom’s own case studies run 42-50% (Linktree: 42%, Robin: 50%).
That 42-50% is what you should plan your invoice against, especially if your content is messy.
One published Intercom case study reports a resolution-time drop from five days and five hours to four hours and 37 minutes after launching Fin.
Where Fin gets expensive is volume.
In one published Intercom example at 15 agents on the Expert plan with Copilot, Proactive Support Plus, and WhatsApp, Expert seats account for $2,085/month, Fin resolutions represent $29,700, Copilot adds $350, Proactive Support Plus adds $99, and messaging contributes about $500, roughly $32,734/month total.
If your monthly resolution volume is north of 20,000 and you don’t have a strong reason to be on Intercom, that’s the point at which you should put Fin, Zendesk AI, and Decagon side by side in a spreadsheet and decide which model wins for your specific volume.
Runner-up: Zendesk AI Agents
If you’re already on Zendesk Suite, Zendesk’s own AI Agents are the right default in 2026, even though the per-resolution math is the worst in this group. The reason is integration tax. Bringing in a second vendor means a second contract, a second admin console, a second analytics surface, and a second team to call when something breaks. Zendesk’s 2026 changes also made the native option meaningfully better.
Until May 2026 the Advanced AI tier was a $50-per-agent-per-month add-on. As of the May 11, 2026 rollout, the Advanced capabilities are absorbing into every Suite/Support plan between May 11 and June 12. The $50 line is going away as a separate SKU, but the per-resolution overage that drives most of the spend stays.
What “Advanced” actually unlocks matters.
The Forethought-derived tier (originally Ultimate.ai) adds a visual dialogue builder with branching block types, generative procedures the agent adapts in real time, authorised actions the agent can take inside Zendesk and connected systems, an integration builder for third-party API calls mid-conversation, and native fluency in 80+ languages.
That’s a real autonomous-agent feature set, not just a smarter Answer Bot.
The per-resolution model is where Zendesk gets uglier than Fin.
Zendesk AI Agent pricing in 2026 is $1.50 per automated resolution committed, or $2.00 pay-as-you-go.
That’s roughly 50-100% more than Fin’s $0.99. Two billing details make the math worse than the rate alone suggests.
January 2026 introduced a critical billing change: automatic overage billing with no prior notification. Before January 2026, resolution overages above your committed monthly volume required manual activation. Since January 2026, Zendesk automatically bills for every resolution above your committed volume at your per-resolution rate.
And the resolution definition itself is loose:
when an AI-handled conversation closes, Zendesk waits 72 hours. If the customer has not re-opened the ticket within that window, the conversation is confirmed as an automated resolution and billed accordingly. The problem: a customer who stops engaging is not the same as a customer whose issue was solved.
If you’re on Suite Professional or Enterprise and Zendesk’s bundled AI is enough for your tier-1 workload, you don’t need to go shopping. If you’re paying full PAYG and your AI volume is above 10,000 resolutions a month, run the comparison against Fin and Decagon before you sign a renewal.
The enterprise option: Ada
Ada is the platform you buy when you’re large enough that “starts around $30,000 a year” isn’t the part of the sentence you flinch at.
At its core, Ada is an enterprise AI customer experience platform built to automate customer service conversations at scale. The company describes itself as “AI-first,” meaning its entire system is built around an AI agent rather than a traditional helpdesk with AI features added afterward. Founded in 2016 and headquartered in Toronto, Ada reports 550+ AI agents deployed globally, 6.4 billion interactions powered, and customers including Monday.com, Pinterest, Square, and Cebu Pacific. It is worth knowing upfront: Ada is designed for large, enterprise-level companies. Their published minimum fit threshold is 300,000 annual conversations.
The reason to consider Ada specifically (rather than Fin or Decagon) is the Reasoning Engine plus Playbooks combination across voice.
The engine driving Ada’s AI is the Unified Reasoning Engine, launched in February 2026. Playbooks are multi-step structured workflows that let Ada’s agents execute service operations using real-time data, without hardcoded scripting. A typical Playbook might walk a customer through an address change: retrieve the order, verify it has not shipped yet, collect the new address, update the record, and confirm the change. As of the February 2026 Reasoning Engine launch, Playbooks are available across voice channels as well as chat and messaging.
The honest downsides are real and worth weighing before a procurement cycle.
The platform learns primarily from formal help-center content. It does not natively ingest unstructured sources such as past support tickets, PDFs, internal wikis, or shared Google Docs. If your team’s most useful knowledge lives outside a structured help center, Ada may return answers that feel incomplete.
And the end-user experience doesn’t match the operator experience.
G2, where support operations managers and platform builders leave reviews, rates Ada 4.6 out of 5. Trustpilot, which reflects end users’ direct chatbot experiences, rates the platform 2.0 out of 5, with recurring complaints about context loss between conversation turns and difficulty reaching a human agent.
Plan a deployment that prioritizes fast handoff, and keep watching that gap.
The high-end pick: Decagon
Decagon is the rest of the enterprise market. It’s the platform you choose when you have a complex omnichannel operation, dedicated engineers to embed with the vendor, and a contract value that would be a rounding error inside a Fortune 500 budget.
Decagon’s customer list reads like a who’s who of tech and consumer brands: Duolingo, Chime, Classpass, Hertz, Oura, Affirm, Dropbox, Notion, and Rippling. The company claims 100+ enterprises and hit a $4.5 billion valuation in March 2026 after raising $250 million in fresh funding.
The technical differentiator is AOPs.
The company’s key differentiator is something called Agent Operating Procedures (AOPs). These let you define agent workflows in natural language rather than code. A non-technical support manager can write instructions like “If a customer asks for a refund over $100, verify their purchase date and escalate to the billing team” and the AI follows that logic.
AI Actions let the agent do things, not just say things. Through integrations with Stripe, Shopify, and Salesforce, Decagon can process refunds, update orders, verify identity, and create tickets, without escalating to a human.
The pricing is the catch.
Decagon does not publicly list its pricing. The figures below are third-party estimates from buyer marketplace data; to get actual numbers, you must request a demo from their sales team. Marketplace data from Vendr provides estimates based on real contracts: these are enterprise numbers. Decagon is not priced for startups or small businesses.
Independent buyer guides put the platform fee around $50,000/year and median annual spend near $400,000.
Decagon’s setup is a structured enterprise engagement with dedicated support staff. Expect about six weeks to full deployment. There is no self-serve option.
If that timeline and shape sound right for your team, the product is genuinely strong. If they don’t, Fin or Ada will get you to a working agent faster and cheaper.
The budget pick: Tidio Lyro
Lyro is the right answer when you’re a small DTC brand or service business that needs an AI agent in front of customers this week and can’t wait six weeks for an enterprise rollout.
Tidio’s Lyro starts with 50 free conversations to see how Lyro handles real customer questions before you commit. Lyro can handle multiple questions in one customer conversation without extra costs. Pay just $0.5 per conversation.
Lyro is powered by Claude (Anthropic AI) and Tidio’s in-house models.
The marketing number is genuine.
Lyro claims it can solve up to 67% of customer problems automatically.
Real-customer deployments are higher when content is good:
For example, Axioma, a UK-based car repair service, achieved an 89% AI resolution rate after implementing Lyro, handling questions about pricing, services, and insurance claims without needing human agent input.
The catch is the same one every Tidio review flags: the sticker price isn’t the real price.
Lyro AI (Tidio’s autonomous AI agent) is a separate paid add-on for all tiers except Premium. It costs $32.50/month for 50 conversations and can significantly increase total monthly costs. Everyone gets 50 free Lyro AI conversations as a one-time trial. After that, you pay $32.50/month for 50 additional conversations. Cost impact example: a 10-person e-commerce business on Growth ($49) adding Lyro AI ($32.50) and Flows automation ($24.17) pays $105.67/month, more than double the advertised price.
And there’s no soft on-ramp from SMB to mid-market inside Tidio.
Tidio’s plan stack jumps from Growth ($59/mo) directly to Plus ($749/mo), a 12x leap with no mid-tier in between. Combined with the 10-seat cap on self-service plans, this is the structural pricing decision that defines whether Tidio fits you.
Plan to grow out of Lyro the same year you grow out of Tidio.
How to choose between them
The decision tree is short. If you’re already standardized on Zendesk Suite and your AI volume fits inside a reasonable committed-resolutions plan, use Zendesk AI Agents. If you’re on any other helpdesk, or you want one agent that works on top of several, start with Fin. If you’re an enterprise with 300,000+ annual conversations, evaluate Ada and Decagon head to head and let the procurement process settle it. If you’re a small ecommerce or service business and the question is “do I have an AI agent at all,” start free with Lyro and accept that you’ll outgrow it. We wouldn’t deploy more than one of these in production at the same time.
