Call center training with AI roleplayYour agents hear the angry caller here first. Not on a live line.
Contact center agents practice complaints, cancellations and escalations with AI callers who interrupt, repeat themselves and lose patience. Every call is scored on your QA form, so coaching starts from evidence.
“I was charged twice this month and nobody has called me back.”
- Greets and verifies
- Acknowledges the problem
- Confirms the facts
- Resolves or sets a time
- Confirms next steps
Why simulate calls
New agents learn on live calls. Your customers pay for it.
Most call center agent training ends with a few shadowed calls, then the live queue. Call simulation gives every agent dozens of hard calls first, each one scored, so the first angry customer is not the first time they hear one.
New-hire nesting
Agents take the calls they will meet in week one, as often as they need, before they go live.
Coaching with practice
A low score on a real call becomes an assigned scenario of the same kind, scored on the same form.
New product, price or policy
The whole floor rehearses the questions a launch or a price change will bring, before the first call comes in.
Call simulation
Six calls every contact center takes. Each with a caller who pushes back.
The AI caller reacts to what the agent says, by voice, the way a customer on the phone would. Every call type has its own criteria from your QA form.
This is my third call about the same router. The third.
I can see both earlier calls, Sofia. I’ll stay on this one until there’s a fix booked.
That’s what the last person said.
Fair. I’m booking the technician now and I’ll text you the slot before we hang up.
- Uses the call history
- Owns the issue
- Commits to an action
- Confirms in writing
I’m moving to a cheaper provider. Just cancel it, please.
I can do that today. Before I do, can I ask what made the price matter now?
We pay for speed we never use.
Then a smaller plan may cost less than the other offer. Shall I compare the two for you?
- Agrees to the request first
- Finds the real reason
- Offers a fitting option
- Respects a firm no
You charged me twice. I want it back today.
You’re right, I see two charges on the 3rd. I’m refunding the second one now.
How long until I see it?
Three to five business days. I’ll email you the reference while we’re still on the call.
- Verifies before details
- Confirms the facts
- Fixes without blame
- Gives a real timeline
Forty people can’t work. Don’t read me a script.
No script. It started at 8:52, engineers are on site, and the next update is at 11.
And if it’s not fixed by then?
Then I call you at 11 myself, with the options for today.
- Gives facts, not filler
- Sets the next update
- Owns the follow-up
- Promises only what it controls
I’ve explained this three times. Put me through to your manager. Now.
I can bring my supervisor in. Can I first tell you what I can do right now?
Fine. Thirty seconds.
I can waive this month’s fee and book the repair for tomorrow morning.
- Doesn’t block the request
- Offers a solution first
- Stays within authority
- Hands over cleanly
Why do you need my date of birth? I just want my balance.
It protects your account. This call is recorded, and I can share details once you’re verified.
Fine. It’s the 14th of March, 1990.
Thank you, Mei, you’re verified. Here is your balance.
- States the recorded-line notice
- Explains why it’s needed
- Verifies before details
- Keeps a friendly tone
More situations, each with an AI character and scoring criteria, are in our role play scenario examples. We build scenarios on any topic, for your industry.
QA scoring
Scored on your QA form. Every call, every line.
Load the form your QA team already uses. The AI fills it in after every practice call, with a timestamp and the agent’s own words as evidence for each item.
“Can I ask what made the price matter now?”1:12Met
“But it’s really a great deal, honestly.”4:18Partial
AI and expert assessorsr = 0.80correlation between AI scores and expert scores on the same conversations
Want your own QA form applied to a call your agents take every day?
Book a demoFor team leads and QA
Know who is ready for the live queue. Before they take it.
A dashboard by agent and call type shows who is ready, who needs another round and which calls trip up the whole cohort.
- Assign the next call from the gap, not from a schedule
- Upload recorded calls and score them on the same QA form
- Connect to any LMS through SCORM or xAPI
FAQ
What contact center leaders ask us. Answered plainly.
Hotels, clinics, restaurants and stores: customer service training.
What training do call center agents need?
Product and system knowledge, and practice in the calls they will take: complaints, cancellations, billing disputes, outages, escalations and verification. The first two come from your own training; AI call simulation covers the practice, as often as each agent needs it.
What is the best training for call center agents?
Training that ends in realistic practice with feedback: agents rehearse each hard call several times, with a score and comments after every run, before they take the real one.
Can we use our own QA form?
Yes. Upload your QA form and call guidelines. Each item becomes a scored criterion with a timestamp and evidence from the call, and required statements can be marked as such.
Do the practice calls sound like real calls?
Yes. Practice runs by voice. The AI caller interrupts, repeats itself, goes silent or loses patience depending on what the agent says, and how hard it pushes is set per scenario.
Can we score real recorded calls?
Yes. Upload recorded calls and they are scored on the same QA form as practice calls, so coaching and practice use one standard.
What is the 80/20 rule in a call center?
A common service-level target: 80% of calls answered within 20 seconds. It measures how fast a call is picked up; practice works on what happens after that.
Which languages can agents practice in?
More than 15, including English and French, so multilingual teams practice in the language they take calls in.
Does the AI judge agents’ emotions?
No. It scores what agents say and how they handle the call; empathy is scored on the content of their replies, such as acknowledging the problem and using the caller’s words. Emotions are modeled only for the AI caller, as part of the scenario.
How long does a practice call take?
Five to twenty minutes, so agents can practice between shifts or in the quiet hours of the queue.
The angry caller, rehearsed. Before the next shift.
Book a short demo. We will load your QA form and run one of your hardest call types with you on the call.