An AI agent for customer service resolves a customer's request instead of only answering it: it reads the order, checks your policy, makes the change in your systems and hands anything else to a human agent with the context. For a consumer brand, the strongest options in 2026 are Flowcall, Sierra, Decagon, Fin (formerly Intercom), Ada, Zendesk AI agents, Salesforce Agentforce, Gorgias, Yuma AI, LimeChat and Yellow.ai, and the right one depends on your channels, the helpdesk you keep and who will build and run the agent.
Every vendor fact below comes from that vendor's own documentation, product pages or pricing page, checked between 27 and 30 September 2026 and linked. We make Flowcall; it's listed first because this list is written for high-volume consumer brands, the buyers Flowcall is built for.
Short answer
- Order, delivery, return and refund requests and product questions on WhatsApp, Instagram, Messenger, email, live chat and phone, with your rules deciding every refund and Flowcall's team building the agent with you: Flowcall.
- A large brand that wants an agent platform built with the vendor and billed on agreed outcomes: Sierra.
- Your CX team writes and changes the procedures in plain language, on chat, email and voice: Decagon.
- Keep the helpdesk you have and add an AI agent to it: Fin.
- A multilingual enterprise brand on an existing CRM or contact-center platform: Ada.
- Already on Zendesk or Salesforce: Zendesk AI agents or Agentforce.
- A Shopify brand: Gorgias for helpdesk and AI from one vendor; Yuma AI to add a specialist agent to the helpdesk you keep.
- A WhatsApp-first D2C brand that also runs WhatsApp marketing: LimeChat.
- A WhatsApp-heavy enterprise that wants to build on one broad platform: Yellow.ai.
What "resolved" means for a consumer brand
Every vendor on this list says its agent resolves requests. For a consumer brand, the test is whether the order, refund or delivery actually changed. Here are six order requests from ecommerce customer service, and what an AI agent has to do before each one counts as resolved:
| Request | The agent reads | It checks, against your rules | It changes | Resolved when |
|---|---|---|---|---|
| "Where's my order?" | The order and the courier's tracking | Whether the parcel is late against your delivery promise | Nothing, or raises a query with the courier | The customer has a delivery date, or the late parcel is escalated to the courier with a deadline |
| Cancel before dispatch | Order status in the store or order system | Not yet shipped; the item can be cancelled | Cancels the order and starts the refund | The order shows cancelled and the refund has started |
| New address on a cash-on-delivery (COD) order | The order and its fulfilment status | Not yet shipped; the new address can be delivered to | Updates the shipping address | The order carries the new address before it ships |
| Damaged item | The order and the customer's photo | Inside the return window; the photo shows damage; past claims | Creates a replacement, a refund or a return pickup | The replacement or refund exists in your system |
| "Where's my refund?" | The return and the refund in the payment system | Whether the refund started, and when the bank usually shows it | Nothing, or passes a failed refund to finance | The customer has the status and a date, or finance has the failed refund with the details |
| Exchange for another size | The order and stock of the new size | Eligible for exchange; the size is in stock | Creates the exchange order and the return | The exchange order exists and the pickup is booked |
Cash on delivery is common in India, where customers pay the courier; it adds address and confirmation work that prepaid orders don't. The first row needs only the right data, read correctly. The other five also need a rule and the right to change something. In a demo, ask each vendor to show the last column in the order or payment system, not only a confirmation in the chat. (For the longer case that the answer isn't the finish line, see our guide to customer service automation.)
Some requests should still end with a human agent: a second damage claim, a refund above your limit, an angry third contact (our guide to escalation management covers the rules). Then the handoff decides whether the customer repeats everything. When Flowcall's AI Agent hands over, it creates a ticket with the conversation, a summary, the customer, the order and what's left to do, and routes it to the right team. In Flowcall's AI Helpdesk that ticket is a Zero-Tab Ticket, with everything needed to finish the job on it. Customer 360 shows the customer's orders, delivery and payments, Agent Assist drafts the reply, and Pre-Filled Actions make the refund or replacement from the ticket, with the form already filled from the conversation. The agent doesn't open Shopify or a courier site to finish the job.
How we chose
We started from the products recommended by the pages that rank for "AI agent for customer service" and kept the ones a support team at a consumer brand could use for order work. We checked each against five questions, using only the vendor's own documentation, product pages and pricing page:
- Does it act, not only answer? It must read live order or account data and change something, within limits you set.
- Where does the AI itself work? We list the channels the agent works on, including WhatsApp, Instagram DMs and voice, not only the ones a helpdesk receives.
- Who decides a consequential action? Whether refunds and cancellations follow instructions the model interprets, deterministic checks, or both.
- How is it tested and reviewed? Simulations before go-live, and quality review after.
- Who builds and runs it? Your admins in a builder, your developers, or the vendor's team.
We left out chatbot builders such as Botpress, Chatbase and Tidio, which our guide to AI chatbots for customer service compares. We also left out helpdesks where AI is one feature among many (see our list of AI customer service software) and voice-only contact-center platforms. We didn't test the products hands-on, and we don't compare prices: each entry names the vendor's pricing model and links its pricing page. After Flowcall, the list runs from standalone agent platforms to agents inside a helpdesk, then ecommerce and WhatsApp specialists; it isn't a ranking. For the wider picture of where AI fits in a support team, see our guide to AI customer service.
AI agents for customer service compared
| Best for | Where the AI works (vendor docs) | How actions are controlled | Who builds it | Pricing model | |
|---|---|---|---|---|---|
| Flowcall | High-volume consumer brands' order, return and refund requests and product questions | WhatsApp, Instagram DMs, Messenger, live chat, email; Instagram and Facebook comments and @mentions; Voice AI agent on calls | Your SOPs as workflows; your rules and approvals must pass before a refund, cancellation or replacement | Flowcall's team, with your approval | Shared on a call |
| Sierra | Large brands that want outcome pricing | Chat, SMS, WhatsApp, email, voice, ChatGPT | Journeys in a no-code studio, or code with the Agent SDK | Your team, with a Sierra agent engineer and product manager | Per agreed outcome |
| Decagon | CX teams that want to own procedures | Chat, email, voice | Agent Operating Procedures: natural language plus code | Your CX team, after an implementation with Decagon | Per conversation or per resolution |
| Fin | Adding an agent to your helpdesk | Chat, email, voice, WhatsApp, Instagram, Messenger, SMS, Slack | Procedures in natural language, with code conditions for critical steps | Your team | Per outcome |
| Ada | Multilingual enterprise brands | Chat, email, SMS, voice, WhatsApp, in-app | Playbooks with ask, set, run and if/else steps | Your CX team, no code | On request |
| Zendesk AI agents | Teams on Zendesk | Messaging and email; WhatsApp and social through Zendesk messaging; calls on supported Talk lines | Generative procedures with conditions and API steps | Your admins | Per automated resolution, plus seats |
| Salesforce Agentforce | Teams on Salesforce | Web chat, SMS, WhatsApp, Messenger, voice | Actions on Salesforce records, flows and APIs | Your admins, in a low-code builder | Per conversation, or credits per action |
| Gorgias AI Agent | Shopify-first brands | Email, chat, SMS, Instagram DMs, Messenger, WhatsApp | You switch on each action and set its conditions | Your team | Per resolved conversation, plus helpdesk plan |
| Yuma AI | Shopify brands keeping their helpdesk | Email, chat, SMS, WhatsApp, Instagram and Messenger through your helpdesk; voice | Agents that follow your SOPs, with hard caps on refunds and coupons | Your team, rolled out in stages you approve | Per fully resolved ticket |
| LimeChat | WhatsApp-first D2C brands | WhatsApp, chat and voice; Instagram and email through add-ons | A hybrid of an LLM and your brand SOP | Your business team, with a dedicated onboarding specialist | Personalised by suite and volume |
| Yellow.ai | WhatsApp-heavy enterprises | WhatsApp, SMS, Instagram, Messenger, email, voice and more | Agents built from natural-language requests, inside guardrails you set | Your team | Free and paid plans; enterprise on request |
The 11 best AI agents for customer service
1. Flowcall
Best for: Consumer brands with high volumes of order, delivery, return, refund and warranty requests, as well as product questions, on WhatsApp, Instagram, Messenger, email, live chat and phone, who want every refund or cancellation decided by their own rules and want Flowcall's team to build the agent and keep improving it with them. Pricing: Flowcall shares pricing on a call.
Flowcall's AI Agent turns your SOPs for returns, refunds, cancellations, exchanges, cash on delivery, damaged products and warranty claims into workflows it follows step by step, starting from ready-made templates for the common ones. It checks current order, delivery, payment and refund data in your systems and completes the work: refunds, cancellations, exchanges, address changes and replacements. Shopify connects natively, and order and courier systems such as Unicommerce, ClickPost and Shiprocket connect through configured connectors. The AI reads the photos and invoices customers send and assesses damage, collects addresses and photos in WhatsApp forms, and follows up when a customer goes quiet.
The same workflows run on WhatsApp, Instagram DMs, Messenger, live chat and email, in the customer's language (more than 100 languages for messaging), and the Voice AI agent answers and makes calls, with a recording, transcript and ticket for every call. On Instagram and Facebook, the AI Agent also sorts the comments and @mentions on your posts and reels, replies publicly from your saved replies and moves support and pre-sales questions into a private DM. Before a customer buys, the same AI on the same WhatsApp number works as an AI shopping assistant, finding and comparing products from your catalogue. After launch, every conversation can be audited, and the requests the AI couldn't resolve are grouped into the workflows, knowledge or integrations worth adding next. Flowcall's team sets up the workflows and integrations and keeps improving them; your team approves each change. If you keep Freshdesk, Salesforce or Sprinklr as your system of record, Flowcall creates and updates tickets there through a connection built for your account.
Not the fit if SMS is your main support channel.
2. Sierra
Best for: Large consumer brands that want an AI agent platform built with the vendor and billed on agreed outcomes. Pricing: outcome-based, on criteria agreed with each customer; not published (Sierra: outcome-based pricing).
Sierra deploys one agent across chat, SMS, WhatsApp, email, voice and ChatGPT (Sierra) in 59 languages, and its agents handle tasks such as returning an order through connections to systems "from order management to CRM" (Sierra product overview). Teams build in Agent Studio's no-code Journeys or, with developers, the Agent SDK, and the Agent Data Platform gives the agent memory of earlier conversations (Sierra: Agent OS 2.0, November 2025). Sierra staffs a dedicated agent engineer and product manager on each deployment to build the agent, integrate your systems and review conversations with your operations team (Sierra: shipping and scaling AI agents). Simulations test an agent against mock customers with different goals, moods and languages, and Sierra says agents should pass them before changes to any journey are published (Sierra: simulations, August 2025).
Limits. The product pages we checked describe connections to systems of record without naming commerce integrations, so ask how the agent reaches your store, order and courier data and which helpdesk it hands over to. Agree what counts as a billable outcome before you sign.
3. Decagon
Best for: Enterprise support teams that want their CX team, not engineers, to write and change the agent's procedures, on chat, email and voice. Pricing: per conversation, or per resolved conversation with no charge for escalations; quoted, not published (Decagon: pricing AI agents).
Decagon's Agent Operating Procedures (AOPs) are workflows written "like training a human on standard operating procedures", which combine "the flexibility of natural language with the reliability of code"; technical teams can version them in Git (Decagon: AOPs). For ecommerce, Decagon lists order tracking, returns and exchanges, subscription updates and account changes, completed in backend systems (Decagon: ecommerce playbook, June 2026). It connects to CRMs such as Salesforce and helpdesks such as Zendesk and Intercom, and a human agent receives "the complete conversation history, any actions the AI attempted, and relevant customer data" (Decagon: setup guide, January 2026). The same guide describes a six-week implementation, from discovery to go-live, worked through with Decagon's team. Its homepage lists simulations at scale and always-on QA (Decagon).
Limits. The Decagon pages we checked name chat, email and voice. If WhatsApp or Instagram DMs carry most of your volume, ask how the agent runs there, and ask which store and order systems it connects to.
4. Fin
Best for: Teams that want to keep their helpdesk (Intercom, Salesforce, HubSpot, Freshworks or another platform) and add an AI agent to it. Pricing: published; charged per outcome (Fin pricing; see our Intercom pricing guide).
Fin works on the Intercom Messenger, email, phone (Fin Voice), WhatsApp, Facebook Messenger, Instagram, SMS and Slack (Intercom: channels for Fin). Procedures handle multi-step requests such as damaged-order claims: you write the steps in natural language and add deterministic controls, and data connectors look things up and take actions in your systems (Intercom: Fin Procedures). For critical actions, Intercom recommends Python code conditions because they are deterministic (Fin: code conditions, updated 9 April 2026). Simulations run a procedure in the background and check whether a data connector fired and how the conversation ended (Fin: simulations, updated 31 July 2026). Fin works with Intercom's own helpdesk or alongside Salesforce, HubSpot, Freshworks and other platforms, though Fin for Ecommerce needs an Intercom helpdesk plan (Intercom: Fin for platforms).
Limits. Read how Fin counts a resolution (below): it includes customers who leave without asking for more help. If you're weighing a move off the Intercom helpdesk, see Intercom alternatives.
5. Ada
Best for: Large, multilingual brands that want a no-code AI agent over an existing CRM or contact-center platform. Pricing: not published; quote on request (Ada pricing).
Ada's AI agent works on chat, email, SMS, voice, WhatsApp and in-app messaging in 60 languages, and connects to Shopify, Salesforce, Microsoft Dynamics, Zendesk, ServiceNow, Genesys and Twilio Flex (Ada for ecommerce). For a return, it can generate a label and update your system, or give the customer a replacement order, a refund confirmation or store credit. Playbooks turn an SOP into step-based workflows: ask the customer, set a variable, run an API tool, branch with if/else; while one runs, the agent watches the conversation and can escalate (Ada docs: Playbooks). CX teams build them in Ada's no-code interface (Ada: Playbooks).
Limits. Prices come only with a quote. The commerce platform Ada names is Shopify; if your orders run through another order or courier system, check the connection.
6. Zendesk AI agents
Best for: Support teams already on Zendesk that want the AI inside the same helpdesk and have admins to build it. Pricing: published; AI agents billed per automated resolution, with helpdesk seats (Zendesk pricing).
Zendesk's AI agents work on messaging and email channels (Zendesk: where you can use AI agents); for WhatsApp, Instagram or Messenger you need Zendesk messaging with that channel connected (Zendesk: AI agents on WhatsApp), and on supported Zendesk Talk lines an AI agent can answer calls (Zendesk: AI agents in Talk). Generative procedures collect details, check a condition and branch, and run an API integration with a fallback when it fails (Zendesk: generative procedures, edited 7 July 2026). Zendesk now sells Forethought's AI agents for other service platforms, and describes built-in QA on every interaction (Zendesk: AI agents).
Limits. To read Shopify orders, the agent needs an API step your team builds (Zendesk: link your AI agent with customer orders). For a side-by-side, see Flowcall vs Zendesk.
7. Salesforce Agentforce
Best for: Service teams whose customer and case data already live in Salesforce. Pricing: published; per conversation, or Flex Credits per action, with per-user options (Agentforce pricing).
Agentforce agents act inside Salesforce: updating records, creating cases, triggering workflows and calling APIs. Agentforce Voice works on the phone, click-to-talk on a website and in mobile apps, and transfers a call to a human agent with the conversation history and customer context (Agentforce Voice). Service agents also work on SMS, WhatsApp and Facebook Messenger (Salesforce: AI customer service agents, July 2026). Testing Center builds test suites from an agent's topics, actions and knowledge and runs them before deployment (Salesforce Help: Testing Center).
Limits. Actions run through Salesforce records, flows and APIs. If your orders live in Shopify or an order system outside Salesforce, ask how that data reaches the agent and who builds the connection.
8. Gorgias AI Agent
Best for: Shopify-first brands that want an ecommerce helpdesk and an AI agent from one vendor. Pricing: published; helpdesk plans by ticket volume, with the AI Agent charged when it resolves a conversation (Gorgias's pricing page; our Gorgias pricing guide explains the plans).
Gorgias's AI Agent works on email, chat, SMS, Instagram DMs, Facebook Messenger and WhatsApp (Gorgias: AI Agent explained, updated in September 2026). It can cancel orders, process returns and update shipping addresses; these actions are opt-in, and you choose which ones it takes and under which conditions. It hands over when it can't respond confidently, meets a sensitive topic or detects frustration, and you can add your own handover rules.
Limits. It's built around Shopify stores, so check how it handles orders that also live in a separate order or warehouse system. Phone support for human agents is an add-on (Gorgias: Voice). If you're comparing ecommerce help desk tools, see Gorgias alternatives.
9. Yuma AI
Best for: Shopify brands that want to keep their helpdesk and add an ecommerce-specialist agent, paying only for tickets it resolves. Pricing: performance-based: you pay for tickets the AI fully resolves; quote on request (Yuma: Support AI).
Yuma works as an automation layer inside the helpdesk you already use, such as Gorgias, Zendesk, Kustomer, Salesforce Service Cloud, Re:amaze or Front. It answers email, live chat, SMS, WhatsApp, Instagram DMs and Messenger, and a newer Voice AI answers your support line with the same agent. It reads and writes Shopify data to edit, cancel or refund orders, and acts in Recharge subscriptions, Loop Returns and shipping tools. Its agents follow your SOPs for refunds, returns and subscription changes, hard limits cap refund and coupon values, and low-confidence replies go to a human agent instead of being sent. Before launch, a playground runs the AI against your past tickets; after launch, a new agent ramps from 1% of tickets to 10%, 30%, 50% and 100%, with your team approving or rolling back each step (Yuma: Support AI).
Limits. Its commerce integrations centre on Shopify and Recharge, and the shipping tools it names are US and European ones; if you sell on another platform or ship with Indian couriers, check the integrations you need.
10. LimeChat
Best for: WhatsApp-first D2C brands that want AI agents on chat and voice for support, alongside WhatsApp marketing, set up with the vendor's onboarding team. Pricing: personalised by suite, volume and automation tier; not published (LimeChat pricing).
LimeChat sells WhatsApp, chat and voice AI agents (LimeChat). Its AI Support Suite puts an AI agent on chat and voice for order tracking, returns, refunds, cancellations and complaints, "powered by hybrid LLM + brand SOP", with image recognition and handoff to live agents. Add-ons cover an omnichannel CRM for email, chat and Instagram, Instagram DMs and comments, and an AI audit of every human and AI conversation. A separate growth suite handles WhatsApp marketing, including COD verification and COD-to-prepaid conversion. LimeChat integrates with Shopify, WooCommerce, CRMs, logistics and returns platforms, supports more than 20 languages, and includes a dedicated onboarding specialist on every plan; LimeChat puts a typical go-live at one to three weeks (LimeChat pricing).
Limits. Ask which refund and cancellation decisions follow your SOP as fixed rules and which the model makes. Per-conversation charges depend partly on the AI agent's resolution rate, so agree how that rate is measured. For a side-by-side, see Flowcall vs LimeChat.
11. Yellow.ai
Best for: Enterprises that want one platform for AI agents across WhatsApp, voice and many other channels, built by their own team. Pricing: free and published entry plans; enterprise pricing on request (Yellow.ai pricing).
Yellow.ai is an official WhatsApp Business Service Provider (Yellow.ai docs: WhatsApp), and its agents also deploy on SMS, Messenger, Instagram, email, Telegram, LINE and other messaging channels (Yellow.ai docs: messaging channels, updated 30 September 2026). For retail, Yellow.ai lists order tracking, exchanges, refunds and cancellations, with integrations such as Zendesk, Freshdesk, HubSpot and Genesys, and chat in 135+ languages (Yellow.ai retail). Its Nexus interface builds agents from requests written in natural language, tests them against thousands of simulated users and fixes problems "within the guardrails you define" (Yellow.ai Nexus).
Limits. Building and maintaining the agents is your team's job. Ask which of Nexus's fixes go live on their own and which wait for your approval, and check the store and courier integrations your orders need.
Also worth a look
- Kustomer: AI agents on chat, email, SMS, WhatsApp and voice, built in AI Agent Studio on each customer's history (Kustomer).
- Gladly: a consumer-brand platform whose AI works on voice and IVR, email, chat, SMS, Messenger, Instagram and WhatsApp; Action Guides act in Shopify and Loop Returns (Gladly help, updated 24 August 2026).
- Kore.ai: an enterprise platform for chat and voice agents that update accounts and complete tasks in back-office systems, aimed at large contact centers (Kore.ai).
How each vendor counts a resolution
Several of these agents are priced on outcomes, and each vendor defines the outcome differently. The definitions below are the vendors' own:
| Vendor | What it counts or charges for |
|---|---|
| Fin | A resolution when, after Fin's last answer, the customer confirms it helped (confirmed) or leaves without asking for more help (assumed); a procedure that ends in a configured handoff is also a billable outcome (Intercom: Fin outcomes) |
| Zendesk | Customer requests the AI agent resolved without escalation to a human agent (Zendesk pricing) |
| Ada | A conversation where the AI agent fully addressed the issue, accurately and safely, without escalating to a human agent (Ada) |
| Sierra | Outcomes such as a resolved conversation or a saved cancellation, on criteria agreed upfront; escalations are usually not charged (Sierra) |
| Decagon | Every conversation, or each fully resolved conversation with escalations free (Decagon) |
| Gorgias, Yuma AI | Conversations or tickets the AI resolves (Gorgias, Yuma) |
| Agentforce | Conversations, or Flex Credits for each action, such as updating a record (Salesforce) |
| LimeChat | Per-conversation charges based on Meta's template categories and the AI agent's resolution rate (LimeChat) |
Each is a reasonable billing rule, and none proves the order was sorted. An assumed resolution can be a customer who gave up, and a conversation that never reached a human agent can still bring the same customer back tomorrow on another channel. So agree your own measure before you sign: count a request as resolved when the change shows in your order, payment or courier system, and the customer doesn't contact you again about the same order within seven days on any channel. Track it by request type, alongside resolution time for the requests that reach your team.
Flowcall reports CSAT for the AI Agent and human agents separately, by channel, next to the AI automation rate. To see why a conversation went wrong, Flowcall's AI Auto QA audits AI conversations, every one or the ones you choose. It flags wrong or made-up answers, loops, missed handoffs and actions the AI wasn't allowed to take, and quotes the conversation in each finding.
Who decides a refund: the model or a rule?
An AI agent follows your policy in one of two ways. It can read instructions written in plain language and interpret them, which copes well with messy conversations. Or it can run deterministic checks, such as "delivered within 7 days" or "refund under your limit", which give the same answer every time. The platforms on this list combine the two, and their documentation shows where each puts the line:
- Fin: natural-language procedures, with Python code conditions that Fin recommends for critical actions.
- Decagon: procedures in natural language that combine with code, versioned in Git.
- Ada: playbook steps that set variables, run API tools and branch with if/else.
- Zendesk: generative procedures with condition checks and API steps.
- Gorgias: actions you switch on, each with the conditions you set.
- Yuma AI: agents that follow your SOPs, with hard caps on refund and coupon values the AI can't exceed.
- LimeChat: an AI agent described as a hybrid of an LLM and your brand SOP.
The question to ask every vendor is the same: for a refund, a cancellation or a replacement, which parts are decided by a rule and which by the model, and can you see which one ran in a given conversation?
Flowcall's answer is the SOP Engine. The AI Agent follows your SOP step by step while the conversation stays natural. Your rules make each decision: eligibility checks, fixed outcomes the AI picks from instead of inventing values, and decisions worked out from order data and the customer's answers. The order, delivery and payment details come from your systems. Once a workflow is set up correctly, it runs the same way every time, and a fix stays fixed. For any conversation, you can see which workflow ran, what data it used and which action it tried.
Test it before it talks to customers
A demo shows the vendor's best case. Before an AI agent goes live on your channels, it should pass tests built from your own conversations, and pass them again after every change. The vendors document this in different ways: Sierra, Fin, Decagon and Yellow.ai run simulated conversations; Agentforce builds test suites in Testing Center; Yuma replays past tickets and then ramps a new agent up in stages, with your team reviewing each one.
Whatever the tool, the test set should include:
- Your top request types, taken from last month's conversations, with the real wording customers use.
- Edge cases: an order that has already shipped, a return one day outside the window, a photo that doesn't show damage, a second claim this month.
- Language switches, such as a customer who starts in English and continues in Hindi, if your customers write that way.
- Failures: an order system that doesn't respond, a refund that fails, a customer who asks for a human agent.
With Flowcall, each workflow runs against simulated customer conversations before it goes live and again after every change. The test cases can be written by AI for the happy path, edge cases and errors, real failures become new tests, and test runs stay out of your live queues, reports and CSAT.
How to choose
- Sort last month's conversations by request type and find the biggest groups. Typical groups are WISMO (where is my order), cancellations, address changes, returns and refunds; count yours rather than assuming.
- Decide whether you keep your helpdesk. Fin, Yuma AI and Ada add an agent to the helpdesk you have; Zendesk, Agentforce and Gorgias put it inside theirs; Flowcall can do either, with its own AI Helpdesk or alongside Freshdesk, Salesforce or Sprinklr.
- Decide who will build and run the agent. Self-serve builders need admin time every time a policy changes; vendor-built agents need a clear approval process on your side.
- Run the six requests from the table above through each shortlisted product, and ask to see the change in your systems. For more demo checks, see our guide to AI customer service for ecommerce.
- Agree how "resolved" will be counted before you sign, and review a sample of AI conversations every week after launch.
Which should you choose?
| If your priority is | Look at |
|---|---|
| Order, delivery, return and refund requests on WhatsApp, Instagram, Messenger, email, live chat and phone, with your rules checked before every refund; the same AI answering product questions on the same number; Flowcall's team building and improving the agent with you | Flowcall |
| An agent platform built with the vendor, billed per agreed outcome | Sierra |
| Your CX team writing and changing procedures itself | Decagon |
| Keeping your helpdesk and adding an agent | Fin or Ada |
| AI inside Zendesk or Salesforce, which you already run | Zendesk AI agents or Agentforce |
| Shopify helpdesk and AI from one vendor | Gorgias |
| An ecommerce specialist inside your current helpdesk | Yuma AI |
| WhatsApp support and WhatsApp marketing from one D2C vendor | LimeChat |
| A self-built platform across many channels, WhatsApp first | Yellow.ai |
| SMS as your main support channel | Sierra, Fin, Gorgias or Yuma AI |
If Flowcall sounds like the fit, book a demo. We'll show Flowcall's AI Agent resolving a return on WhatsApp, the rule behind each decision, and what your team sees when a conversation is handed over. Qualifying brands get a free proof of concept on the service problem they most need solved, built with their team and tested before anything goes live.
Frequently Asked Questions
Are there AI customer service agents?
Yes. AI customer service agents answer customers on chat, messaging, email and phone, look up their orders or accounts, take actions such as cancellations and refunds within your rules, and hand the rest to human agents. The eleven products above are examples; they differ in channels, how actions are controlled and who builds them.
How do you create an AI agent for customer service?
Start with one request type your team handles often, such as order cancellations. Write the policy as steps: what to check, what the customer may get, and when a human agent takes over. Connect the systems the agent needs to read and change, test it on real past conversations, then launch on one channel and review conversations weekly. You can build it in a self-serve platform, with developers on a framework, or with a vendor that builds it for you.
Who are the big 4 AI agents?
There's no agreed "big four" in customer service. If you mean general AI assistants, the best known are ChatGPT, Gemini, Claude and Microsoft Copilot; none of them is a customer service agent on its own. Among customer service agents, Ada and Zendesk appear in three of the four vendor lists that ranked for this search in September 2026 and Fin in two, with newer platforms such as Sierra and Decagon in one each.
How can I use AI in customer service?
The most common uses are an AI agent that resolves routine requests, AI that drafts replies and summaries for human agents, routing that sends each ticket to the right team, and quality review of every conversation. Where to start depends on your volume and channels; our guide to agentic AI for customer service covers how far autonomous agents go today.
What's the difference between an AI agent and a chatbot?
A chatbot answers from a script or your help content. An AI agent also reads live data, takes actions within your rules and hands over with the context when it can't finish. Many products sold as chatbots now do some of both, so judge a product by what it does with an order. Our guide to chatbot vs conversational AI explains the technology.
How much does an AI agent for customer service cost?
Vendors charge per resolution or outcome, per conversation, per action, or through helpdesk seats with AI added, and some combine them; the table above names each vendor's model and links its pricing page. On WhatsApp, Meta also charges per delivered message: for template messages and, since 1 October 2026, for the agent's replies after 1,000 free service messages a month per business phone number, as covered in our guide to WhatsApp Business API pricing. Flowcall shares pricing on a call.
Can an AI agent work on WhatsApp?
Yes. Flowcall, Sierra, Fin, Ada, Gorgias, LimeChat, Yellow.ai and others run their agents on WhatsApp. A business can reply freely only within 24 hours of the customer's last message; after that it must use an approved template, which a WhatsApp chatbot has to allow for.
Will AI agents replace human agents?
Not for a consumer brand with real exceptions. An AI agent takes over the requests your rules can settle, which changes what human agents spend their day on: judgement calls, upset customers and exceptions. We look at the wider question in will AI replace customer service.
