Supercharge Contact Center Agent Performance with Real-Time Agent Assist™

Accelerate agent onboarding, surface 2X more accurate information in real-time and enable autonomous learning for support agents.
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The Problem With Other Contact Center Software

Other quality management systems rely on keywords and info scattered across multiple tools, which require constant updates and result in unacceptably high inaccuracies. Real-time Agent Assist™ understands customer intent with 2X the accuracy of keyword-based systems and provides agents with guidance using your best resources for each scenario.

"Level AI has been a pleasure to work with. The user interface and tool are easy to use with practical features built-in. Their conversation intelligence platform is unlike anything we have seen in this space. We truly see Level AI as a partner."

Chris Lewis
Product Manager

Key Features

Improve call center agent performance

Enable Autonomous Learning & Coaching

Level AI enables autonomous learning for agents by evaluating every interaction across voice calls, email and chat. Agents can review their scores, keep track of their most important metrics, and learn how to improve performance without 1:1 human coaching.

Custom FAQs For Unique Scenarios

Level AI Scenarios show useful hints to agents throughout a conversation, such as greeting the customer during the beginning of the conversation, confirming their identity, rephrasing their problem before suggesting the solution, and much more.
Custom FAQs For Unique Scenarios

AI That Learns From Agent Feedback

Your agents can train Level AI by providing feedback. Our models learn and provide better results over time. If Agent Assist™ doesn’t help with a customer issue, agents can flag it.

Integrate With Your Favorite Tools and Document Formats

Level AI scours through all your knowledge sources and surfaces proactive hints to help agents provide the right answers in real-time. Integrate your existing knowledge bases with ease and don’t sweat the format.
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FAQs

Reliable data, conversation monitoring software, and analytics are the tools call centers need to evaluate agent performance. Most call centers use common metrics to evaluate agent performance, such as:

  • Customer Satisfaction (CSAT)
  • First-Call Resolution
  • Service Level Percentage
  • Average Handle Time (AHT)
  • Abandon Rate
  • Cost

Call center software, such as Level AI, provide insights from existing data and an interface that allows call center leaders the ability to monitor agent performance across support channels. Additionally, Level AI allows contact center teams to build custom reports from other data sources, such as BI (business intelligence) tools.

The best contact center analytics are designed to uncover meaningful insights, organize your most important metrics, and answer questions about call center agent performance from a single location.

Here are 7 ways to improve call center agent performance:

  1. Adopt advanced NLU (natural language understanding) software that understands customer intent. For example, Level AI uses NLU to provide contact center agents answers and solutions to almost any customer inquiry in real-time with exceptional accuracy. Most CCaaS (call center as a service) software relies on NLP (natural language processing) technology. NLP models rely on keyword matching, which is highly inaccurate and time consuming.
  2. Eliminate avoidable calls. By providing solutions to the most common customer issues without involving a live agent, you’ll give agents more time to spend on the most important customer support issues.
  3. Train call center agents in real-time with AI software. Use advanced contact center software that can train your agents in real-time, such as Level AI. This allows for independent learning and reduced agent onboarding times.
  4. Monitor a higher percentage of call center agent conversations. You can monitor more support conversations with technology that can accurately monitor more than 1-2% of agent conversations. Level AI, for example, accurately monitors 100% of agent conversations.
  5. Use the best call center metrics for your business. Re-examine your call center metrics, make sure your goals are clear and agents know how they are being evaluated. A great way to manage and communicate your most important call center metrics is to maintain a QA (quality assurance) scorecard.
  6. Utilize call center analytics tools. Know what’s happening in your call center with analytics that can accurately report your KPIs and house data from multiple BI (business intelligence) tools in one location.
  7. Build call center quality assurance rubrics over time. Provide call center agents a clear process for solving common problems and utilize modern contact center software to learn how to solve more complex customer support scenarios.

Call center software is typically separated into two categories based on where it’s hosted: on-site, or in the cloud. Cloud-based contact center software is now commonly referred to as CCaaS, or Contact Center as a Service.

Until recently, the large majority of call centers still used locally installed software. However, in 2022, the majority of companies have either adopted or are planning to adopt cloud-based solutions, such as Level AI.

To further break down the type of software call center agents use depends on whether the call center is primarily inbound, outbound, or a mixture of the two. Additionally, not all call centers are simply making voice calls. Many contact centers use a mixture of voice call software, email software, and chat software.

CCaaS software has become popular largely due to new platforms that offer contact centers the ability to monitor the performance of their agents across all communication channels. Level AI, for example, monitors 100% of support agent conversations across voice calls, email, and chat.

Call center software is typically separated into two categories based on where it’s hosted: on-site, or in the cloud. Cloud-based contact center software is now commonly referred to as CCaaS, or Contact Center as a Service.

Until recently, the large majority of call centers still used locally installed software. However, in 2022, the majority of companies have either adopted or are planning to adopt cloud-based solutions, such as Level AI.

To further break down the type of software call center agents use depends on whether the call center is primarily inbound, outbound, or a mixture of the two. Additionally, not all call centers are simply making voice calls. Many contact centers use a mixture of voice call software, email software, and chat software.

CCaaS software has become popular largely due to new platforms that offer contact centers the ability to monitor the performance of their agents across all communication channels. Level AI, for example, monitors 100% of support agent conversations across voice calls, email, and chat.

Workforce management (WFM) in a call center refers to the strategies and technologies companies use to optimize call center agent efficiency. Call center WFM includes a set of processes that ensure the right number of agents with the right call center skills are scheduled at the right time.

What does workforce management software do? Call center WFM solutions, such as Level AI, integrate with your support software to provide a data-driven approach to agent performance and training, QA (quality assurance), and process management.

Companies that use workforce management strategies often see reduced employee churn, improved customer satisfaction, and reduced operational costs.

Improve Contact Center Agent Performance with Agent Assist™

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How To Evaluate AI for Modern Contact Centers