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4.7 (200+ reviews)

Turn every coaching opportunity into better agent performance

Give agents the practice they need before handling real customers. Level AI Coaching Simulation turns identified performance gaps into realistic customer conversations, with feedback based on your existing QA standards.

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Traditional training fails to prepare agents for complex customer conversations

As automated systems and AI bots handle more routine inquiries, support agents take on an increasing proportion of complex interactions, from escalations and disputed transactions to high-stakes service failures. Traditional training & occasional role-plays offer limited preparation for these conversations.

Coaching depends on managers

As contact center teams operate with leaner management, supervisors have more agents to coach and less time for individual sessions. Every mock call requires their involvement, limiting how much practice agents receive.

Scripted scenarios fail to replicate customer friction

Scripted exercises follow predictable paths. They leave agents underprepared for customers who interrupt, push back, or become frustrated during a conversation.

Coaching lacks hands-on practice

QA identifies recurring performance gaps, but these findings rarely turn into targeted practice. Agents continue making the same mistakes without opportunities to correct them.

Prepare agents to deliver better
customer experiences

QA identifies recurring performance gaps, but these findings rarely turn into targeted practice. Agents continue making the same mistakes without opportunities to correct them.Move beyond limited mock calls with realistic customer simulations built from real situations where agents have previously struggled, repeatable practice, and feedback grounded in your quality standards.

Automation

Training

Quantity

Standard

New Hire

Reduce recurring errors on critical calls

Reduce quality issues by addressing the specific failure points identified in production. Coaching Simulation uses AutoQA findings to generate realistic simulation calls for agents who need targeted practice on those specific behaviors.

Keep training aligned with production QA

Ensure practice performance directly reflects in customer conversations. Coaching Simulation applies your existing AutoQA rubric to practice conversations, giving supervisors a consistent way to assess performance.

Coach more without adding supervisor workload

Increase coaching volume across large teams without pulling supervisors away from live floor operations. Coaching Simulation delivers assigned practice scenarios directly to agents & updates agent progress records asynchronously.

Prepare agents for difficult customer conversations

Reduce repeat contacts and escalated complaints by preparing agents to handle frustrated customers, unexpected objections, and challenging conversations with confidence. Coaching Simulation recreates customer behavior from past interactions, letting agents practice responding to interruptions, pushback, and escalating situations.

Get new hires ready for live calls faster

Protect customer satisfaction by verifying agent competence before they go live on the floor. New hires practice common customer issues and workflows through realistic simulations and receive immediate feedback on their performance and areas for improvement.

“Working with Level AI was a breath of fresh air after a miserable “failure to launch” with another vendor. We were able to make more progress in 4 weeks with Level AI than we had in 6 months previously. I love how responsive the implementation and development teams have been. The user experience has been excellent, and uptake and feedback from our users has been stellar."

Ben Huber

Director, Professional Services - Topcon

“Working with Level AI was a breath of fresh air after a miserable “failure to launch” with another vendor. We were able to make more progress in 4 weeks with Level AI than we had in 6 months previously. I love how responsive the implementation and development teams have been. The user experience has been excellent, and uptake and feedback from our users has been stellar."

Ben Huber

Director, Professional Services - Topcon

“Working with Level AI was a breath of fresh air after a miserable “failure to launch” with another vendor. We were able to make more progress in 4 weeks with Level AI than we had in 6 months previously. I love how responsive the implementation and development teams have been. The user experience has been excellent, and uptake and feedback from our users has been stellar."

Ben Huber

Director, Professional Services - Topcon

FAQ

Frequently Asked Questions

Any more questions?

Contact us

What is Level AI Coaching Simulation?

Coaching Simulation is an AI-based practice experience for contact center agents. It recreates customer conversations so agents can rehearse challenging situations, receive structured feedback, and work on their skills before applying them in live interactions. 

How are simulation scenarios created?

Trainers can create scenarios using instructions and relevant policy documents to define the situation, expected customer behavior, and procedures agents should follow during practice.

How realistic are the simulated conversations?

The AI plays the role of a customer based on the scenario's instructions and persona. Training scenarios can represent behaviors such as frustration, interruptions, objections, and escalations so agents practice responding to changing conversation dynamics.

How are agents evaluated during simulations?

After each simulation, Level AI evaluates the conversation using AutoQA and the defined QA rubric. The evaluation identifies strengths, missed expectations, and areas where an agent needs additional practice.

Can agents repeat simulations to improve their performance?

Yes. Agents can practice an assigned scenario as many times as they need, and every attempt is scored so they can see what to fix before facing a similar call with a real customer.

Supervisors can also keep retries from becoming a memory exercise. In each scenario's advanced settings, there are two options:

  • Vary the scenario on retries: each attempt changes small details, such as amounts, phrasing, and the customer's opening line, so an agent can't just memorize and replay a failed attempt.

  • Randomize the customer's voice: each attempt uses a different voice, so agents practice the skill itself instead of getting used to one speaker.

That means each retry feels like a new conversation while still testing the same skill.

Can agents repeat simulations to improve their performance?

Yes. Agents can practice an assigned scenario as many times as they need, and every attempt is scored so they can see what to fix before facing a similar call with a real customer.

Supervisors can also keep retries from becoming a memory exercise. In each scenario's advanced settings, there are two options:

  • Vary the scenario on retries: each attempt changes small details, such as amounts, phrasing, and the customer's opening line, so an agent can't just memorize and replay a failed attempt.

  • Randomize the customer's voice: each attempt uses a different voice, so agents practice the skill itself instead of getting used to one speaker.

That means each retry feels like a new conversation while still testing the same skill.

How does Coaching Simulation reduce the workload for supervisors?

Agents practice conversations independently, reducing the need for a supervisor to participate in every mock call. Automated evaluations give supervisors a starting point for reviewing performance and focusing their coaching sessions.

FAQ

Frequently Asked Questions

What is Level AI Coaching Simulation?

Coaching Simulation is an AI-based practice experience for contact center agents. It recreates customer conversations so agents can rehearse challenging situations, receive structured feedback, and work on their skills before applying them in live interactions. 

How are simulation scenarios created?

Trainers can create scenarios using instructions and relevant policy documents to define the situation, expected customer behavior, and procedures agents should follow during practice.

How realistic are the simulated conversations?

The AI plays the role of a customer based on the scenario's instructions and persona. Training scenarios can represent behaviors such as frustration, interruptions, objections, and escalations so agents practice responding to changing conversation dynamics.

How are agents evaluated during simulations?

After each simulation, Level AI evaluates the conversation using AutoQA and the defined QA rubric. The evaluation identifies strengths, missed expectations, and areas where an agent needs additional practice.

Can agents repeat simulations to improve their performance?

Yes. Agents can practice an assigned scenario as many times as they need, and every attempt is scored so they can see what to fix before facing a similar call with a real customer.

Supervisors can also keep retries from becoming a memory exercise. In each scenario's advanced settings, there are two options:

  • Vary the scenario on retries: each attempt changes small details, such as amounts, phrasing, and the customer's opening line, so an agent can't just memorize and replay a failed attempt.

  • Randomize the customer's voice: each attempt uses a different voice, so agents practice the skill itself instead of getting used to one speaker.

That means each retry feels like a new conversation while still testing the same skill.

Can agents repeat simulations to improve their performance?

Yes. Agents can practice an assigned scenario as many times as they need, and every attempt is scored so they can see what to fix before facing a similar call with a real customer.

Supervisors can also keep retries from becoming a memory exercise. In each scenario's advanced settings, there are two options:

  • Vary the scenario on retries: each attempt changes small details, such as amounts, phrasing, and the customer's opening line, so an agent can't just memorize and replay a failed attempt.

  • Randomize the customer's voice: each attempt uses a different voice, so agents practice the skill itself instead of getting used to one speaker.

That means each retry feels like a new conversation while still testing the same skill.

How does Coaching Simulation reduce the workload for supervisors?

Agents practice conversations independently, reducing the need for a supervisor to participate in every mock call. Automated evaluations give supervisors a starting point for reviewing performance and focusing their coaching sessions.

FAQ

Frequently Asked Questions

Any more questions?

Contact us

What is Level AI Coaching Simulation?

Coaching Simulation is an AI-based practice experience for contact center agents. It recreates customer conversations so agents can rehearse challenging situations, receive structured feedback, and work on their skills before applying them in live interactions. 

How are simulation scenarios created?

Trainers can create scenarios using instructions and relevant policy documents to define the situation, expected customer behavior, and procedures agents should follow during practice.

How realistic are the simulated conversations?

The AI plays the role of a customer based on the scenario's instructions and persona. Training scenarios can represent behaviors such as frustration, interruptions, objections, and escalations so agents practice responding to changing conversation dynamics.

How are agents evaluated during simulations?

After each simulation, Level AI evaluates the conversation using AutoQA and the defined QA rubric. The evaluation identifies strengths, missed expectations, and areas where an agent needs additional practice.

Can agents repeat simulations to improve their performance?

Yes. Agents can practice an assigned scenario as many times as they need, and every attempt is scored so they can see what to fix before facing a similar call with a real customer.

Supervisors can also keep retries from becoming a memory exercise. In each scenario's advanced settings, there are two options:

  • Vary the scenario on retries: each attempt changes small details, such as amounts, phrasing, and the customer's opening line, so an agent can't just memorize and replay a failed attempt.

  • Randomize the customer's voice: each attempt uses a different voice, so agents practice the skill itself instead of getting used to one speaker.

That means each retry feels like a new conversation while still testing the same skill.

Can agents repeat simulations to improve their performance?

Yes. Agents can practice an assigned scenario as many times as they need, and every attempt is scored so they can see what to fix before facing a similar call with a real customer.

Supervisors can also keep retries from becoming a memory exercise. In each scenario's advanced settings, there are two options:

  • Vary the scenario on retries: each attempt changes small details, such as amounts, phrasing, and the customer's opening line, so an agent can't just memorize and replay a failed attempt.

  • Randomize the customer's voice: each attempt uses a different voice, so agents practice the skill itself instead of getting used to one speaker.

That means each retry feels like a new conversation while still testing the same skill.

How does Coaching Simulation reduce the workload for supervisors?

Agents practice conversations independently, reducing the need for a supervisor to participate in every mock call. Automated evaluations give supervisors a starting point for reviewing performance and focusing their coaching sessions.

Resources

Tools and insights to improve every customer interaction

View all resources

Voice of the Customer Insights

Inferred Customer Satisfaction (iCSAT): methodology and applications

Inferred CSAT datasheet

Voice of the Customer Insights

Inferred CSAT datasheet

Voice of the Customer Insights

Ultimate guide for upleveling your customer experience program for the generative AI age

Voice of the Customer Insights

Inferred Customer Satisfaction (iCSAT): methodology and applications

Inferred CSAT datasheet

Voice of the Customer Insights

Inferred CSAT datasheet