Verify Customer Identity: 7 Best AI Support Agents (2026)

Created time

Sep 29, 2026 02:04 PM

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Author

Mike Heap

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Oct 5, 2026

Ecomm?

What does it take for an AI agent to verify customer identity?

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TL;DR: Six jobs: know which requests need a check, recognize a customer who is already signed in, check one who isn't, share or change nothing until the check passes, hand failed or suspicious checks to a person, and let your team see who was checked.

Verifying the customer breaks down into six separate jobs, and most tools do some of them well and leave the rest to you. These are the six I scored every tool against.

Six jobs an AI agent has to cover to verify a customer, as six cards in a grid: knows which requests need a check, recognizes a signed-in customer, checks a customer who isn't signed in, shares or changes nothing until the check passes, hands over when a check fails or looks wrong, and lets your team see what happened.

1. It knows which requests need a check

A request such as "What card is on my account?" or "change my email" needs a check, because the answer discloses something private or changes the account. The AI can answer "What's your refund policy?" for anyone.

I want to be able to say in plain language which request types need a check, and have the AI follow it, so everyday questions get a quick answer and account details stay with the person they belong to. A subscription app might answer billing-date questions for anyone

2. It recognizes a customer who is already signed in

When a customer is logged in on your site or app, or writes from the email address on the account, the AI should know who they are without asking again. Asking a signed-in gamer to prove who they are before they can see their balance feels broken to them.

Getting this right usually means someone on your side connects your sign-in to the AI once. In the tools I looked at, it's a short piece of developer work. It removes the check entirely for every customer who is signed in.

3. It checks a customer who isn't signed in

Email and signed-out chat are where the AI has to run the check itself. Of the six jobs, this is the one where I saw the widest spread between tools. The AI needs a way to confirm the account holder inside the conversation, using a code sent to the email or phone already on file or details only the owner would know, checked against your records.

Security questions on their own are weak, because the answers are often easy to guess or find. A large study of account recovery found it next to impossible to write secret questions that are both secure and memorable, and US federal guidance on digital identity steers services away from them.

4. It shares or changes nothing until the check passes

Account details stay locked until the check passes, and after a pass the AI shares only what the request needs (a question about a withdrawal shouldn't reveal the customer's home address). Once a customer has passed, they shouldn't be asked again in the same conversation. The rule to hand your security reviewer is that nothing account-specific is disclosed or changed before a pass, and the AI never has more access than the customer does.

5. It stops and hands over when a check fails or looks wrong

Some checks should end with a person. Repeated wrong answers, a request to change the very email or phone number a code would go to, or a customer saying "I didn't ask for this" all belong with your team straight away.

The handover should include the conversation so far, so your agent doesn't start from scratch. And asking for a person should always work, whether or not the check passed.

6. Your team can see who was checked and what the AI did

Afterwards, your team should be able to see whether a check happened, how it happened and what the AI shared or changed. When a customer says "I never asked for that refund", that record is how you answer them.

Any job a tool leaves out becomes work your team does by hand, so test all six in a demo.

How did I score these tools for verifying customer identity?

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TL;DR: Eight criteria, each scored out of 10: the six jobs above, plus how much work setup takes and what the tool costs a month at 1,000 account tickets, summed to a total out of 80.

The scores come from each vendor's help articles, product pages, pricing pages and customer stories. Six criteria are the jobs in the last section, and two more cover what it takes to go live and what it costs.

The criteria, in the order they matter for this job:

Knows when to check - whether you can say which requests need a check and the AI follows it

Recognizes signed-in customers - whether a customer signed in on your site, app or email is known without being asked again

Checks customers who aren't signed in - whether the AI can confirm the account holder inside an email or signed-out chat

Shares only after a pass - whether account details and changes stay locked until the check passes

Hands failed checks to a person - rules for failed or suspicious checks, an always-available route to a person, and a summary on handover

Shows what was checked - whether your team can see afterwards who was checked, how, and what the AI did

Setup effort - the time and people needed to go live, assuming your team uses AI to draft the rules and steps

Monthly cost at 1,000 account tickets - the lowest plan that covers the volume, monthly, on one declared basis

Each criterion is scored out of 10 and the eight scores add up to the Overall, out of 80. Phone support isn't scored. Where a tool's pages show it covers calls, I say so in its section.

The 7 AI customer service agents that verify customer identity at a glance

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TL;DR: My AskAI leads on 63 out of 80, with Intercom Fin second on 60 for its ready-made code check and Fini third on 59 as the only tool whose pages show all six jobs.

Here are the eight scores for each tool, ordered by total from left to right:

(scores out of 10)	My AskAI	Intercom Fin	Fini	Chatbase	Ada	Zendesk AI agents	Decagon
Knows when to check	9	8	8	7	8	6	7
Recognizes signed-in customers	8	8	8	8	8	8	6
Checks customers who aren't signed in	6	9	7	5	5	4	6
Shares only after a pass	8	9	9	8	9	7	7
Hands failed checks to a person	9	7	8	6	7	6	8
Shows what was checked	8	6	9	7	6	8	7
Setup effort	7	7	5	6	5	6	4
Monthly cost at 1,000 account tickets	8	6	5	9	2	4	2
Overall	63	60	59	56	50	49	47

Same eight criteria, in plain words:

Criterion	My AskAI	Intercom Fin	Fini	Chatbase	Ada	Zendesk AI agents	Decagon
Knows when to check	Task triggers, plain-language rules	Check set per connection	Stronger check, sensitive actions	Signed-in-only actions	Sign-in where data's sensitive	Procedures hand to check	Controlled operations
Recognizes signed-in customers	Email sender or signed-in chat	Signed-in chat, developer setup	Signed-in widget, email lookup	Website sign-in, developer setup	Sign-in step	Web and app chat	Not shown for chat
Checks customers who aren't signed in	Task checks your records	Emailed code, chat and email	Checks before account changes	Guest order lookups	Asks for the account email	Relies on sign-in	Voice authentication
Shares only after a pass	Proceeds only after confirmation	Data only after code	Mismatches go to review	Payments need signed-in customer	Sign-in before sensitive data	Restricted answers when signed-in	Strict controls
Hands failed checks to a person	Handover step plus summary	Failure route, no summary	Escalates with full context	Ask-for-a-person trigger	Error answer, some summaries	Escalation flows you design	Transfer with summary
Shows what was checked	Echo and Inspect	Approvals in conversation	Every action logged	Log by user and action	Audit logging named	Verified check mark	Reasoning trace
Setup effort	Helpdesk app, developer step	Admin switch, developer sign-in	Live in 14 days	Self-serve, new widget	Enterprise build	Admin plus developer	Built with Decagon's team
Monthly cost at 1,000 account tickets	About $263 on Pro	$693 to $990	Growth plan fee	$150 on Standard	Sales only	$1,350 plus seats	Sales only

My AskAI leads on two jobs. It puts the check only in front of the requests that need one, and it gets a failed or suspicious check to a person with the conversation attached. Its bill is also the lowest published one after Chatbase. Intercom Fin beats us on customers who aren't signed in, because its code check comes built in where ours is a Task your team sets up.

I put Intercom Fin second on the strength of the only ready-made check in this set that works by email as well as chat. Fini is the one tool whose pages show all six jobs, and it would score higher if its pricing page printed the Growth plan's monthly fee. Of the tools that publish prices, Chatbase has the lowest bill at this volume (about $150 a month on Standard), and it suits a small team that doesn't run a helpdesk yet.

Where does AI identity verification go wrong?

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TL;DR: Three ways: the AI takes a name or an email address at face value, it checks so often that real account holders give up, or it lets someone change the contact details a check depends on.

Here are the three failures to test for in any demo, and what good looks like for each.

Three-card grid of identity check failure modes: takes the customer's word for it, checks everyone so genuine customers give up, lets someone change the details the check relies on.

Failure mode 1: It takes the customer's word for it

An AI that takes a single detail typed into the chat as proof, such as a name, an order number or an email address, will hand account details to the wrong person. Zendesk's authentication article warns that an email typed into a form or an AI agent's prompt could belong to someone else. People fall into the same trap: one analysis of bank call centers found agents almost always ask whichever check question is easiest for the customer.

In a demo, I ask for a balance or an address after giving nothing but an email address, and watch what comes back. Look for a real check against your records before anything is shared.

Failure mode 2: It checks everyone, so genuine customers give up

A code before a policy answer, or a second check after the customer already passed one, pushes people to ask for a person or leave. On one helpdesk's community forum, a support team asked for a way to let customers verify their email once instead of every day.

Check only where the request needs one, and let a pass last the whole conversation. Intercom, for example, doesn't ask again within 30 minutes. My view is that it should always be easy to reach a person, whether or not the customer passed.

Failure mode 3: It lets someone change the details the check relies on

Changing the email or phone number on file, then passing the next check sent to the new details, is the classic takeover route. A US consumer-protection alert describes scammers calling a phone provider's customer service and asking for the number to be moved to a phone they own. US rules for phone carriers bar checks that rely on readily available account or biographical details.

I keep these with a person at first. A change to contact details should always need a stronger check or a person, and a note should go to the old address when the change goes through. If the email on the account changes mid-conversation, the AI should check again.

Can My AskAI verify customer identity?

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TL;DR: My AskAI runs inside the helpdesk you already use and covers 5 of the 6 jobs fully, strongest at deciding which requests need a check and at sending failed checks to a person. Your team sets up the check for signed-out customers in a Task, and 1,000 account tickets come to about $260 a month on Pro, Task replies included.

We built My AskAI to work inside the helpdesk your team already runs: Zendesk, Intercom, Freshdesk, Freshchat, Gorgias or HubSpot. It installs as an app from each helpdesk's marketplace, so your team keeps its inbox and routing, and account requests are handled next to every other ticket.

The My AskAI homepage hero, pitching an AI customer service agent within your helpdesk, with a red 'Create AI Agent' button.

Most account questions need no check, and the AI answers those from your help content, Custom Answers and historic tickets. The check applies only to the requests you name.

How does My AskAI check who it's talking to?

Checks run inside a Task, a multi-step workflow you describe in plain language. You give each Task example messages that should start it and examples that shouldn't, so "change my email" starts the check and "what's your refund policy?" gets an answer straight away. Guidance adds plain-language rules for topics that go straight to a person. You pick every request type that gets a check, so knowing when to check scores 9, the top mark for that job.

We use User Data to give the AI the customer's account details, such as their plan, subscription or recent orders, when your helpdesk has already identified them. That covers an email from the address on the account and a chat where your helpdesk knows the customer is signed in. Signed-in chat depends on your helpdesk's sign-in being connected by a developer. Recognizing signed-in customers scores 8, level with five others.

For a customer who isn't signed in, your team sets up a Task that asks for details your process uses, such as an order number and its postal code. The Task checks both against your records through a Tool. Checking customers who aren't signed in scores 6 for us and 9 for Intercom Fin, because its code step is built in and ours is a check your team builds. Each Task step can say "only proceed after confirmation", and each action can run automatically or wait for a teammate to approve it, which puts sharing only after a pass at 8.

Video preview — AI Agent Tasks & Tools (Refunds, Orders)

We send a failed check to a person. A Task can hand over at any step, for example when a customer keeps struggling to confirm their contact details, and customers can ask to speak to a person at any time. Before the handover, the AI writes a summary of the conversation, and it stays out of the ticket until your team hands it back. No tool here scores higher than our 9 for handing failed checks to a person.

Afterwards, your team can ask Echo, the assistant in our dashboard, why the AI answered or acted as it did, and Inspect & Logs shows the user data and guidance it used for any conversation. I give that an 8 for showing what was checked, since Fini's per-step log is the one clearer record in this set.

Setup scores 7, tied for top: the Task is written in plain language, and a developer connects the Tool to your records once. Writing the Task is quick if you paste your current check process into an AI tool and ask it for steps. You can then run the whole thing in internal-note mode first, so your team reads every proposed reply before a customer does.

Capabilities shipped (out of 6)

Job	My AskAI
Knows which requests need a check	✅ Task triggers and Guidance rules in plain language
Recognizes a customer already signed in	✅ email sender or helpdesk-verified chat
Checks a customer who isn't signed in	⚠️ a Task that checks your records
Shares or changes nothing until the check passes	✅ proceeds only after confirmation, automatic or approved
Hands failed or suspicious checks to a person	✅ handover inside the Task, summary, always reachable
Team can see who was checked	✅ Echo and Inspect & Logs

Who's using My AskAI for account requests?

Three of our customer stories show parts of this setup in use. An iGaming operator on Intercom connected live player data from its systems through User Data, which feeds its payments Tasks, and rolled the AI out progressively.

A digital-goods marketplace, also on Intercom, uses a named Task for each common ticket type, including accounts blocked by a verification check. The Tasks work out which case the customer is in and give them the right answer. A creator-monetization platform on Zendesk keeps its trust and safety tickets with people.

What does My AskAI cost at 1,000 account tickets a month?

We charge $199 a month for Pro, with 1,000 credits included, then $0.12 a credit, and it covers up to 5,000 tickets a month. I've assumed 600 account tickets arrive by chat and 400 by email, each with two AI replies, which is a typical ticket for us. A chat ticket like that uses 1 credit and an email ticket 1.5, so 1,000 tickets use 1,200 credits. That's $199 plus the extra credits at $0.12, or $223.

We bill Tasks at $0.02 a reply on top, and both replies are part of the check Task, which adds $40. That comes to about $260 a month, or roughly $0.26 a ticket, and the price is the same whether the AI finishes the ticket or hands it over. Cost scores 8, behind only Chatbase's lower bill. The 30-day trial unlocks every feature with unlimited tickets and no card, so you can prove it on real account requests before you pay.

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Choose My AskAI for verifying customers if:

Your team works in Zendesk, Intercom, Freshdesk, Freshchat, Gorgias or HubSpot and wants checks handled there.

You want to decide request by request which questions need a check and which go straight to a person.

You want each account action to run automatically or wait for approval, chosen per action.

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Don't choose My AskAI for verifying customers if:

Most of your account requests come by phone and you want the AI to take the calls.

You want the vendor's team to design and build the whole check for you.

For more on My AskAI, see our Tasks and Tools page, our User Data page and our pricing page.

Can Intercom Fin verify customer identity?

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TL;DR: Intercom Fin has the only ready-made code check in this set that works by email and chat, and covers 5 of the 6 jobs. Its record of each check is thin, and Fin costs $0.99 per outcome, or $693 to $990 a month at this volume.

Fin is Intercom's AI agent. It runs inside Intercom, or on another helpdesk with a minimum monthly commitment, and it also covers the phone through Fin Voice.

The Intercom homepage hero, titled 'A complete system for human and AI customer service', with 'Start free trial' and 'View demo' buttons.

How does Intercom Fin check who it's talking to?

Before Fin looks up a customer's data, it can email a code to the address on file. The customer replies on the same email thread or types the code into chat, and gets three attempts (each code lasts 10 minutes). Nobody else here offers a ready-made check that works in both channels, so Fin gets the top score of 9 for checking customers who aren't signed in.

It stops short of 10 only because Intercom labels the feature a beta, and a customer with no email on file can't use it. The data lookup runs only on a correct code, the pass lasts 30 minutes, and a changed email triggers a fresh code. Those three rules earn a 9 for sharing only after a pass.

You turn the code on for each data lookup, and Intercom pitches its Procedures for identity verification. I find a setting per data lookup a little coarser than choosing by request type, so knowing when to check scores 8. Signed-in chat customers can be recognized once a developer secures Intercom's chat, and I give that an 8 as well.

When the code fails three times, expires or has no email to go to, a workflow can send the customer down a failure route. Fin hands over when a customer clearly asks for a person, but Procedures can't write an automatic summary note on handover, and with no human routing target set up Fin offers no handover at all. Those gaps hold handing failed checks to a person at 7. In a trial, I check the routing target first.

Intercom's articles describe approval answers recorded in the conversation and logs for each data lookup, but not a record of whether each code check passed. That puts showing what was checked at 6. Setup scores 7: the code check is an admin setting and Procedures are written in plain language, but the signed-in path needs a developer.

Capabilities shipped (out of 6)

Job	Intercom Fin
Knows which requests need a check	✅ code switched on per data lookup
Recognizes a customer already signed in	✅ signed-in chat, developer setup
Checks a customer who isn't signed in	✅ emailed code in email and chat, three tries
Shares or changes nothing until the check passes	✅ data only after a correct code
Hands failed or suspicious checks to a person	✅ failure route, escalation rules
Team can see who was checked	⚠️ approvals recorded, no check record shown

Who's using Intercom Fin for account requests?

Of the Intercom stories I read, Rocket Money comes closest to account work. It started Fin on 10% of conversations and widened it to carefully scoped jobs, including account access requests. Fin now resolves 68% of the conversations it's involved in. At Fundrise, Fin resolves 50% of support volume.

What does Intercom Fin cost at 1,000 account tickets a month?

Intercom prices Fin at $0.99 per outcome, and a completed Procedure counts as an outcome even when it ends in a handover. By my reading, that means a failed check that ends with a person can still be billed. If Fin finishes 700 of the 1,000 tickets, that's $693 a month, rising to $990 if every handed-over ticket also completed a Procedure. Intercom seats come on top, as they would for any AI you run in Intercom.

Fin's bill goes up as it closes more tickets, so cost scores 6. It's published and self-serve, but it's the highest published bill here after Zendesk's.

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Choose Intercom Fin for verifying customers if:

You want a ready-made code check you can switch on without building it.

Many of your account requests arrive by email from customers who aren't signed in.

You also want AI on the phone from the same vendor.

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Don't choose Intercom Fin for verifying customers if:

You need a clear record of every check for disputes or audits.

You want the monthly bill to stay the same as the AI closes more tickets.

For more on Intercom Fin, read our complete guide to Fin, browse the Intercom Fin alternatives roundup or see how it compares with My AskAI.

Can Fini verify customer identity?

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TL;DR: Fini is the only tool here whose pages show all 6 jobs, with a stronger check before every sensitive action and every step logged. Growth charges $0.89 per resolved ticket past a monthly allowance, so at 700 resolved tickets you'd pay the Growth plan fee on its own.

Fini is built for fintech support teams and works alongside helpdesks including Zendesk, Intercom, Gorgias and HubSpot. Its finance page covers voice, chat and email.

The Fini homepage hero, pitching a self-learning AI agent that Fini says resolves 90% of support tickets, with a Book a demo button and resolution-rate, accuracy, language and monthly-resolution figures.

How does Fini check who it's talking to?

Fini's finance page promises a stronger identity check before any sensitive action, every time. I like how clear that rule is, and it scores 8 on knowing when to check, a point behind My AskAI because Fini's public pages don't show how you pick which requests need one.

Signed-in customers can be recognized in Fini's chat widget, and Fini can look a customer up in your helpdesk by email, so recognizing signed-in customers earns an 8. For customers who aren't signed in, the Atlas story lists identity checks before account changes, and Fini says it can fully automate a phone-number change once the customer passes. The public pages show the checks happening, though not what the customer is asked, which puts checking customers who aren't signed in at 7. A phone-number change is the one I keep with a person longest, so ask Fini's team how it decides a pass is strong enough.

I score sharing only after a pass at 9, because in the Atlas story any mismatch goes to human review. Fini also hands over with the full context, so handing failed checks to a person scores 8. Its public pages describe escalation on a mismatch but not a route for a customer who simply asks for a person.

Its record is the most detailed in the set. Fini says every action is logged, including the data pulled, the policy applied and the step taken, so its 9 for showing what was checked is the top score for that job. In a dispute, the log lets your team show the customer which data the AI pulled and which step it took.

Setup scores 5. Fini says customers go live in 14 days and are fully autonomous in 30, but I marked it down because the rollout is demo-led and signed-in widget users need a developer.

Capabilities shipped (out of 6)

Job	Fini
Knows which requests need a check	✅ stronger check before any sensitive action
Recognizes a customer already signed in	✅ signed-in widget, helpdesk lookup by email
Checks a customer who isn't signed in	✅ identity checks before account changes
Shares or changes nothing until the check passes	✅ mismatches go to human review
Hands failed or suspicious checks to a person	✅ escalates with the full context
Team can see who was checked	✅ every action logged

Who's using Fini for account requests?

Atlas, a fintech, went from 15% to 70% automation across its main support journeys, including identity checks and account changes. Wefunder uses Fini for account work such as password resets and two-factor fixes.

What does Fini cost at 1,000 account tickets a month?

Fini's pricing page says each plan includes a monthly allowance of tickets, well above 700 on Growth, and Growth charges $0.89 for each resolved ticket past it.

So at this volume, what you'd pay is the Growth plan's monthly fee. Cost scores 5 because the page doesn't print that fee, so ask Fini for it before you compare.

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Choose Fini for verifying customers if:

You run fintech support and want a stronger check before every sensitive action.

You need a detailed log of what the AI pulled and did for each customer.

Your account requests come in by voice as well as chat and email.

❌

Don't choose Fini for verifying customers if:

You want to see the full monthly price before you talk to sales.

You want to set up and test the AI yourself this week.

For more on Fini, read our complete guide to Fini or browse the Fini alternatives roundup.

Can Chatbase verify customer identity?

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TL;DR: Chatbase recognizes customers signed in to your website and locks payment actions until they are, covering 4 of the 6 jobs. Of the tools that publish prices, it has the lowest bill at this volume, about $150 a month on Standard, but you run chat in its own widget.

Chatbase is an all-in-one AI chat tool with a chat widget and helpdesk of its own, so adopting it means running chat in Chatbase. For a small team with no helpdesk yet, that's often a plus, and it can hand tickets to Zendesk, Freshdesk, Gorgias, Intercom and HubSpot.

The Chatbase homepage, pitching conversational AI agents that resolve issues across chat, email and voice, with a Procedures panel showing Order return and refund, Order status lookup and Upgrade plan switched on and Cancel subscription switched off.

How does Chatbase check who it's talking to?

Chatbase's Identity Verification feature lets the AI know a customer who is logged in to your website, once your developer connects it. That scores 8, level with most of the set. I think it's the simplest version of that job here.

For built-in shop actions you mark each one as signed-in only or open to anyone, which scores 7 on knowing when to check (a point below Fini and Intercom Fin, because anything outside those actions needs a custom procedure). A customer who isn't signed in can look up a shop order with their checkout email or phone and order number. Any other check is a procedure you build, so checking customers who aren't signed in scores 5.

Payment actions require a signed-in customer, so sharing only after a pass scores 8. Those actions only work in its website chat, which keeps it off 9.

A customer can ask for a person and the AI adds a summary to the ticket (a teammate can also take over and stop the AI). A handover on a failed check is something you build into the procedure, so handing failed checks to a person scores 6. Showing what was checked gets a 7: the activity log filters by customer and by action result (full audit logs are Enterprise-only).

Setup scores 6: it's self-serve and quick to start, but the signed-in check needs a developer and you're moving chat into a new widget. You can also show the AI to a percentage of website visitors, so you can roll it out gradually.

Capabilities shipped (out of 6)

Job	Chatbase
Knows which requests need a check	✅ each shop action marked signed-in only or anyone
Recognizes a customer already signed in	✅ website sign-in, developer setup
Checks a customer who isn't signed in	⚠️ guest order lookups, custom procedures
Shares or changes nothing until the check passes	✅ payment actions need a signed-in customer
Hands failed or suspicious checks to a person	⚠️ ask-for-a-person trigger and summary
Team can see who was checked	✅ activity log by customer and action

Who's using Chatbase for account requests?

Aplazo, a buy-now-pay-later provider in Mexico, uses Chatbase to sign up merchants, and half of the inbound merchants it wins now come through it. Jumia used it to scale support for its network of independent sales agents across eight African markets. Both stories are about sales and agent support, and neither shows the checks I scored above.

What does Chatbase cost at 1,000 account tickets a month?

Chatbase's monthly plans are Hobby at $40 for 700 credits, Standard at $150 for 4,000 and Pro at $500 for 15,000. Standard is the lowest plan with Chatbase's helpdesk and the payment actions scored above. I've priced it on a model that uses one credit per reply, so 1,000 tickets at two replies each use 2,000 credits, well inside Standard's 4,000.

A pricier model uses two credits per reply, which takes the same volume to 4,000 credits, still $150. Every extra call the AI makes to run an action costs more credits, and past 4,000 each 1,000 costs $40, so the bill can climb. It's the lowest published bill here, so cost scores 9, and that climb keeps it off 10.

✅

Choose Chatbase for verifying customers if:

You're a small team without a helpdesk and want chat, AI and ticketing in one tool.

Your customers sign in to your website before they ask about their account.

You want the lowest published monthly bill.

❌

Don't choose Chatbase for verifying customers if:

You already run a helpdesk and want the AI to work inside it.

Many of your account requests come by email from customers who aren't signed in.

For more on Chatbase, read our complete guide to Chatbase, browse the Chatbase alternatives roundup or see how it compares with My AskAI.

Can Ada verify customer identity?

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TL;DR: Ada documents a clear sign-in step before its AI shares anything sensitive and covers 4 of the 6 jobs. It's an enterprise build with sales-only pricing, and its record of each check is thin.

Ada is an enterprise AI agent that covers chat, messaging apps, email and voice, and hands over to helpdesks including Zendesk, Gorgias and Freshchat. That breadth makes it a strong fit if your customers reach you on the phone and in messaging apps as well as in chat.

The Ada homepage hero, titled 'The agentic customer experience platform', with a 'Speak to an expert' button.

How does Ada check who it's talking to?

Ada's sign-in docs say that sign-in confirms the customer is who they claim to be, and that it should happen before the AI shares any sensitive data. Sharing only after a pass scores 9 for that rule. The same docs tell you to ask for sign-in where data is sensitive or the account changes, which scores 8 on knowing when to check.

Once a customer signs in, Ada's tools act as that customer, so the AI can reach nothing in the account that the customer couldn't reach themselves. I give that an 8 on recognizing signed-in customers.

For a customer who isn't signed in, Ada's Playbook docs show a verify-identity step that asks for the account email, passes it to a check you connect to your own system and branches on the result. I like the branching, but you build that check yourself, and the docs example asks for nothing beyond an email address, which on its own is weak proof. That puts checking customers who aren't signed in at 5, level with Chatbase and one below My AskAI, whose example asks for two details.

When sign-in fails, Ada gives an error answer, and a failed tool step hands the conversation off. Ask to see that failure path in a demo before you sign.

Handover summaries only exist on some helpdesks, so handing failed checks to a person scores 7. Ada's trust page names audit logging, but for a dispute I want a record of the check inside the conversation, and its docs describe none, so showing what was checked scores 6.

Setup scores 5, because it's an enterprise implementation and the sign-in step needs a developer on your side.

Capabilities shipped (out of 6)

Job	Ada
Knows which requests need a check	✅ sign-in where data is sensitive or the account changes
Recognizes a customer already signed in	✅ sign-in step, tools act as the customer
Checks a customer who isn't signed in	⚠️ Playbook step you build, email-only example
Shares or changes nothing until the check passes	✅ sign-in before any sensitive data
Hands failed or suspicious checks to a person	✅ error answer and handoff, summaries on some helpdesks
Team can see who was checked	⚠️ audit logging named, no check record shown

Who's using Ada for account requests?

Brigit, a financial health app, reports 40% ticket resolution with Ada. Its case study describes how the team built trust in the AI before letting it answer customers.

What does Ada cost at 1,000 account tickets a month?

Ada's pricing page publishes no prices and leads to a demo booking. One procurement marketplace puts the median Ada contract at $72,000 a year, which is well above anything else priced here. Sales-only pricing with no monthly figure scores 2 on cost.

✅

Choose Ada for verifying customers if:

You want a documented sign-in step with a clear failure path.

Your customers reach you across chat, messaging apps and voice.

You have the budget and team for an enterprise rollout.

❌

Don't choose Ada for verifying customers if:

You want published pricing and a self-serve start.

You need a record of each check your team can open per conversation.

For more on Ada, read our complete guide to Ada, browse the Ada alternatives roundup or see how it compares with My AskAI.

Can Zendesk AI agents verify customer identity?

⚡

TL;DR: Zendesk AI agents recognize customers signed in to your website or app and flag them for your agents, but cover only 3 of the 6 jobs. Customers who aren't signed in are left to whatever process you have, and 1,000 account tickets cost about $1,350 a month on top of seats.

Zendesk AI agents run inside Zendesk and are included on every Suite plan from Suite Team, with voice available too. If your team already runs Zendesk, they're the AI built into the tool you know.

The Zendesk AI agents page hero, titled 'Self-improving AI agents built for resolution', with a 'Start your free trial' button and a 14-day free trial note.

How do Zendesk AI agents check who they're talking to?

Once a customer is signed in through your site or app, Zendesk's AI agents don't ask for their name or email again, and your agents see a green check mark beside each message they send. With that check mark, an agent picking up the ticket can see at a glance which customers are signed in (and which still need a check). It earns the 8 on recognizing signed-in customers and the 8 on showing what was checked, both held there because the sign-in only covers Zendesk's web chat and mobile app messaging.

For a customer who isn't signed in, Zendesk's answer is to get customers signed in. Checking customers who aren't signed in scores 4, the lowest in the set. If a lot of your account requests arrive by email, I think that leaves your team checking most of them by hand. AI answers from restricted help articles are shown only to signed-in customers, which scores 7 on sharing only after a pass.

Generative procedures can hand off to a shared identity verification step. Your admins decide which requests need a check by building flows (a job for someone comfortable in Zendesk's builder), so knowing when to check gets a 6. Escalation flows are yours to design and can be removed entirely, and Zendesk's escalation articles don't mention a handover summary, so handing failed checks to a person also scores 6.

Setup scores 6, because it needs both an admin in Zendesk and a developer to connect your sign-in to Zendesk's messaging.

Capabilities shipped (out of 6)

Job	Zendesk AI agents
Knows which requests need a check	⚠️ procedures hand off to a shared check step
Recognizes a customer already signed in	✅ web and app chat, not asked again
Checks a customer who isn't signed in	❌ relies on the customer being signed in
Shares or changes nothing until the check passes	✅ restricted answers only for signed-in customers
Hands failed or suspicious checks to a person	⚠️ escalation flows you design, no summary shown
Team can see who was checked	✅ green check mark beside signed-in messages

Who's using Zendesk AI agents for account requests?

Babbel uses Zendesk AI agents and reports an AI automation rate above 50% across its general support volume.

What do Zendesk AI agents cost at 1,000 account tickets a month?

Zendesk bills per automated resolution on top of Suite seats, at $2.00 pay-as-you-go or $1.50 on a commitment, with 5 included per agent each month on Suite Team. I've modeled a five-agent team: 700 resolutions minus 25 included is 675 billable, or $1,350 a month pay-as-you-go. That's the highest published bill here, and it grows as the AI resolves more, so cost scores 4.

✅

Choose Zendesk AI agents for verifying customers if:

Most of your customers are signed in to your website or app when they ask.

You want your agents to see at a glance which customers are signed in.

You want the AI built into Zendesk itself.

❌

Don't choose Zendesk AI agents for verifying customers if:

Many account requests come by email or from customers who aren't signed in.

You want the cost to stay the same as the AI resolves more tickets.

For more on Zendesk AI agents, read our complete guide, browse the Zendesk AI alternatives roundup or see how it compares with My AskAI.

Can Decagon verify customer identity?

⚡

TL;DR: Decagon names identity verification among the operations it runs under strict controls and offers voice authentication, covering 4 of the 6 jobs. It's an enterprise build with sales-only pricing.

Decagon is an enterprise AI agent for chat, email and voice that works with helpdesks including Zendesk and Intercom. Its product overview lists identity verification among the critical operations it runs securely and with strict controls.

The Decagon homepage hero, titled 'The AI concierge for every customer', with a work email field and a 'Get a demo' button.

How does Decagon check who it's talking to?

As I read its pages, Decagon runs checks through rules you set with its team, including rules for escalation across chat, voice and email. That scores 7 on knowing when to check, below Fini and Ada, because the public pages describe the controls in general terms.

Its security page describes flexible authentication methods for voice, and short-lived access to your systems for each session. I look for that second part in any tool with account access, because it means the AI can't keep reaching into an account once the conversation is over. The public pages don't show how a signed-in chat customer is recognized or how a chat or email customer is checked, so Decagon scores 6 on both. Its finance page stresses validation and auditability, which puts sharing only after a pass at 7.

Decagon hands over to a person, and on voice it passes the call across with a short summary. That's worth an 8 for handing failed checks to a person. You can trace the agent's reasoning and review its behavior afterwards, so showing what was checked gets a 7. I think that trace is useful when a customer disputes what the AI did.

Setup scores 4, the lowest here, because implementation is demo-led and built with Decagon's team.

Capabilities shipped (out of 6)

Job	Decagon
Knows which requests need a check	✅ identity verification under strict controls
Recognizes a customer already signed in	⚠️ per-session access, chat sign-in not shown
Checks a customer who isn't signed in	⚠️ voice authentication, chat and email not shown
Shares or changes nothing until the check passes	✅ strict controls, validation
Hands failed or suspicious checks to a person	✅ escalation, voice transfer with summary
Team can see who was checked	✅ reasoning trace and review

Who's using Decagon for account requests?

Chime, a fintech, reports 70% resolution across chat and voice with Decagon. Its finance page lists jobs from password resets and balance questions to fraud alerts and disputes.

What does Decagon cost at 1,000 account tickets a month?

Decagon's own post on pricing describes charging per conversation or per resolution without giving a rate. Like Ada, it scores 2 on cost.

✅

Choose Decagon for verifying customers if:

A large share of your account requests arrive by phone.

You want the vendor's team to build and run the rollout with you.

You're an enterprise fintech with budget for a custom build.

❌

Don't choose Decagon for verifying customers if:

You want to see the price before a sales call.

You want to set up and test checks yourself.

For more on Decagon, read our complete guide to Decagon, browse the Decagon alternatives roundup or see how it compares with My AskAI.

What does automating identity checks save you? (worked example)

⚡

TL;DR: At 1,000 account tickets a month, handling every one by hand costs about $2,400, and the published AI options run from about $150 to $1,350 on the cheapest plan that covers the volume.

The basis for every row is 1,000 account tickets a month, meaning requests where the account holder has to be confirmed before the answer or the change. I've assumed 600 arrive by chat and 400 by email, each with two AI replies, a typical ticket. The AI finishes 700 and 300 go to a person, such as failed checks and contact-detail changes.

For the no-AI row, I've assumed six minutes of team time per ticket for a team that already uses AI to help where a person does the work. That's priced at $0.40 a minute, which allows for overheads on top of the median US wage for customer service representatives of $21.53 an hour.

Scenario	Plan modeled	Monthly cost	Effective $/ticket	Notes
No AI	Your team handles every ticket	$2,400	$2.40	1,000 tickets × 6 minutes × $0.40
My AskAI	Pro	$263	$0.26	$199 + 200 extra credits at $0.12, plus $40 of Task replies; 30-day free trial
Intercom Fin	Per outcome	$693 to $990	$0.69 to $0.99	700 outcomes at $0.99, up to 1,000 if every handover completes a Procedure; seats extra
Zendesk AI agents	Suite Team, pay-as-you-go	$1,350	$1.35	675 resolutions at $2.00 after 25 included for five agents; seats extra
Fini	Growth	Growth plan fee	-	700 resolved tickets fall inside Growth's monthly allowance; $0.89 per resolved ticket past it; fee not printed on the pricing page
Decagon	Sales only	Not published	-	Pricing by quote
Ada	Sales only	Not published	-	Pricing by quote
Chatbase	Standard	$150	$0.15	2,000 credits on a one-credit model, 4,000 on a two-credit model; lowest plan with its helpdesk and payment actions

On these assumptions, every AI row also leaves your team 300 tickets to handle, about $720 a month of team time at the same rate, so it doesn't change the order. Without AI, part of the six minutes each ticket takes goes on confirming who is asking before any real work starts.

On the per-outcome and per-resolution rows, the bill goes up with every account ticket the AI closes. My AskAI charges per ticket whether the AI finishes it or hands it over, and add-ons such as Tasks bill on top on every plan, which is why our row includes the $40 of Task replies. Our ROI calculator runs the same sums on your own volume.

So which AI customer service agent is best for verifying customer identity?

⚡

TL;DR: My AskAI is the pick for teams that want checks set request by request inside their current helpdesk, Intercom Fin is the runner-up for a switch-on code check by email and chat, and Fini is the wildcard for fintech teams that want a stronger check before every sensitive action.

We top the scoreboard on 63. Our AI answers the questions that need no check, puts the check in front of the requests you name, and sends every failure to a person with a summary, all inside Zendesk, Intercom, Freshdesk, Freshchat, Gorgias or HubSpot.

Intercom Fin, on 60, is the pick if you want a code check today and many of your account requests arrive by email. Fini, on 59, suits a fintech team that wants the vendor to run a stronger check before every sensitive action and log every step. Chatbase is a sound, low-cost start for a small team with no helpdesk yet. If most of your account requests come by phone, Decagon and Ada are the ones to look at.

Whichever tool you choose, I'd roll it out in this order:

Let the AI answer the account questions that need no check, such as policies and order status.

Let it answer signed-in customers from their account details.

Test the check out of customers' sight first, so your team reads every proposed step before a customer does.

Keep contact-detail changes with a person until you trust the checks.

Send every failed check to a person, always.

The iGaming operator we work with followed the same idea and rolled the AI out progressively on top of live player data. The digital-goods marketplace gives each common ticket type its own Task. To see how a Task checks a customer before it acts, try My AskAI free for 30 days on your own account requests.

FAQs

How do you verify a customer's identity?

Check what the person tells you against details already on your records, or send a code to the email or phone already on the account. Security questions on their own are weak, because the answers are often easy to guess or find. In my view, you should only check where the request discloses or changes something, so everyday questions stay quick.

Can an AI agent verify a customer's identity by itself, or does the customer need to be logged in?

Both are possible. Most tools here can recognize a signed-in customer once your developer connects your sign-in, and we also treat an email from the address on the account as verified. For customers who aren't signed in, Intercom Fin emails a code, Ada's Playbooks can ask for the account email and pass it to a check you build, Fini runs identity checks before account changes, and in My AskAI we run a Task that checks the details against your records.

Which requests actually need a check?

Order status, opening hours and policy questions need no check. Anything that reveals private account details or changes the account does, such as billing or card details, a withdrawal, or a new email, phone number or address. Changes to contact details need the strongest check or a person (I treat them as the riskiest request of all), because they're the usual route into a takeover.

What does the AI do when a check fails, and when does a person take over?

A good setup stops and hands the conversation to a person with a summary, without making the customer start again. Intercom Fin sends the customer down a failure route after three wrong codes, Ada gives an error answer on a failed sign-in, and Fini sends mismatches to human review. In My AskAI, we let a Task hand over at any step, and customers can ask to speak to a person at any time.

Can it verify someone over email as well as chat?

Yes, with the right tool. Intercom Fin's code works by replying on the same email thread, and we treat an email from the address on the account as verified. Zendesk's sign-in covers its web chat and mobile app messaging, and Chatbase's payment actions only work in its website chat.

How to verify customer identity over the phone?

The same six jobs apply on the phone, and one contact-center glossary describes passive checks that confirm a caller without asking them anything. In this set, Decagon, Ada, Fini, Intercom Fin, Zendesk and Chatbase all show a voice channel on their pages.

What are the best practices for customer authentication?

Seven that cover most support teams:

Check only where the request discloses or changes something.

Confirm every name, email address or order number against your records.

Don't rely on security questions alone.

Let one pass last the whole conversation.

Treat contact-detail changes as the riskiest request.

Send failed checks to a person with a summary.

Keep a record of every check and what the AI did.

7 Best AI Customer Service Agents to Verify Customer Identity (2026)

What does it take for an AI agent to verify customer identity?

1. It knows which requests need a check

2. It recognizes a customer who is already signed in

3. It checks a customer who isn't signed in

4. It shares or changes nothing until the check passes

5. It stops and hands over when a check fails or looks wrong

6. Your team can see who was checked and what the AI did

How did I score these tools for verifying customer identity?

The 7 AI customer service agents that verify customer identity at a glance

Where does AI identity verification go wrong?

Failure mode 1: It takes the customer's word for it

Failure mode 2: It checks everyone, so genuine customers give up

Failure mode 3: It lets someone change the details the check relies on

Can My AskAI verify customer identity?

How does My AskAI check who it's talking to?

Capabilities shipped (out of 6)

Who's using My AskAI for account requests?

What does My AskAI cost at 1,000 account tickets a month?

Can Intercom Fin verify customer identity?

How does Intercom Fin check who it's talking to?

Capabilities shipped (out of 6)

Who's using Intercom Fin for account requests?

What does Intercom Fin cost at 1,000 account tickets a month?

Can Fini verify customer identity?

How does Fini check who it's talking to?

Capabilities shipped (out of 6)

Who's using Fini for account requests?

What does Fini cost at 1,000 account tickets a month?

Can Chatbase verify customer identity?

How does Chatbase check who it's talking to?

Capabilities shipped (out of 6)

Who's using Chatbase for account requests?

What does Chatbase cost at 1,000 account tickets a month?

Can Ada verify customer identity?

How does Ada check who it's talking to?

Capabilities shipped (out of 6)

Who's using Ada for account requests?

What does Ada cost at 1,000 account tickets a month?

Can Zendesk AI agents verify customer identity?

How do Zendesk AI agents check who they're talking to?

Capabilities shipped (out of 6)

Who's using Zendesk AI agents for account requests?

What do Zendesk AI agents cost at 1,000 account tickets a month?

Can Decagon verify customer identity?

How does Decagon check who it's talking to?

Capabilities shipped (out of 6)

Who's using Decagon for account requests?

What does Decagon cost at 1,000 account tickets a month?

What does automating identity checks save you? (worked example)

So which AI customer service agent is best for verifying customer identity?

FAQs

Start using AI customer service in your business today

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