Best Call Center Quality Assurance (QA) Software 2026. (Updated)

Introduction

Every contact center has a quality program. Very few can say it covers most of their customer conversations. According to McKinsey research manual QA typically evaluates only 1-5% of customer interactions, while a largely automated QA process can achieve more than 90% accuracy, compared to 70-80% for manual scoring. In other words, manual sampling isn’t just slower, it’s also less accurate.

The business case for automation is just as strong. The same McKinsey analysis found that generative AI has the potential to yield more than 50% savings in quality assurance costs, alongside a 25-30% increase in agent efficiency and a 5-10% improvement in customer satisfaction. And QA is about to get more complex: Gartner predicts that agentic AI will autonomously resolve 80% of common customer service issues without human intervention by 2029, which means quality programs must evaluate AI agents alongside human ones.

In this guide, we compare the 13 best call center quality assurance software platforms for 2026, covering what each does best, where it falls short, how much it costs, and which type of contact center it fits. We’ll start with Level AI, our own platform, which analyzes 100% of customer interactions using intent-based AI rather than keyword matching.The contact center QA platforms we’ll explore are:

What is call center quality assurance software?

QA software monitors, evaluates, and improves the performance of call center agents and the overall customer experience. It typically includes:

1. Quality management (QM) features like scorecards, calibrations, and reporting to help teams meet compliance requirements, coach agents, and manage performance.

2. Automated scoring to reduce reliance on manual review.

3. Voice of the Customer (VoC) metrics, by sending out surveys or analyzing customer interactions to derive feedback, sentiment, and predictive insights (e.g., churn risk and NPS).

While these features describe what the software does, it’s important to understand how QA fits into the bigger picture. QA itself is a process within the broader program of quality management (QM). The evaluations and scores generated by QA and contact center automation tools produce the data QM leaders need for coaching, compliance, and continuous improvement.

In other words, a QA process provides tactical activities, like scoring interactions, monitoring performance, and capturing insights based on call recordings, while QM uses that information strategically to improve customer experience, drive training, and make operational decisions.

Similarly, most people understand QA to exclusively pertain to past interactions, whereas call monitoring software focuses on listening to live conversations to check service quality, ensure compliance, and guide agents in real time.

Must-have features to look out for in a call center quality assurance tool

Below, we compare features from different competitors to help you assess which tool best suits the needs of your business. If you’ve got more time for reading, we provide more detailed descriptions of these tools further down in the article below.

Leading call center quality assurance software

1. Level AI: best for turning conversation data into actionable QA insights

Level AI provides a single, integrated QA platform that uses natural language understanding and semantic intelligence to analyze conversations with near-human accuracy, evaluating 100% of interactions rather than just a small sample.

This ensures our advanced AI continuously learns from every customer touchpoint and gives QA teams a channel-agnostic view of the customer journey. Instead of analyzing text messages in one silo and voice interactions in another, Level AI connects the dots across all channels, delivering consistent, personalized experiences across multiple systems.

Level AI uses this unified intelligence to surface patterns, detect risks, and recommend coaching moments so QA analysts, coaches, and team leads can take targeted, informed actions to improve agent performance and drive better call center efficiency.

Our advanced AI also moves beyond outdated keyword-based systems to grasp the true intent, emotional tone, and contextual meaning of customer interactions, even when the language is indirect or nuanced.

This means fewer missed signals, more accurate evaluations, and a deeper understanding of both agent performance and customer sentiment. Level AI delivers not only post-interaction QA analysis, but also allows you to monitor calls for quality in real time using our Real-Time Manager Assist.

Below, we go into detail on how our system delivers measurable improvements in agent performance, customer satisfaction, and operational efficiency.

Understanding what customers want and how they feel

Level AI’s Scenario Engine detects and classifies customer intent by understanding the context of the conversation. This allows it to evaluate full conversational journeys to uncover deeper intent, needs, and emotional drivers.

For instance, when a customer says “I was charged twice” in a recorded conversation, the Scenario Engine understands that the customer ultimately wants a refund, and classifies this as a “Customer Refund” scenario.

Scenarios are indicated in our call transcripts as conversation tags, which are searchable and filterable so you can create curated lists of conversations where a particular intent was expressed.

This helps you isolate and review conversations related to specific intents to better identify patterns or recurring issues behind such requests, such as product defects, unclear billing policies, or service failures.

It also helps you coach more effectively by, for example, reviewing how different agents handle similar situations, then using those insights to standardize best practices.

Thanks to its semantic intelligence, Level AI also detects how customers are feeling during conversations, and currently identifies eight different emotions, the highest number of emotions of any other QA software.

These include:

• Anger

• Annoyance

• Disapproval

• Disappointment

• Worry

• Happiness

• Admiration

• Gratitude

Similar to conversation tags, our sentiment analysis tools incorporate sentiment tags to highlight instances where a given emotion occurred in conversation; these are similarly searchable and filterable for conversation analysis and reporting.

The platform auto-scores customer sentiment during conversations by assigning an overall Sentiment Score ranging from 0 to 10, with 0 being the most negative and 10 the most positive.

This is the result of a weighted calculation emphasizing the emotions a customer expresses later in the conversation, such as after an issue’s resolution, as these better reflect a customer’s lasting feelings about both your brand and the agent’s performance.

For example, if a customer begins a call frustrated about a billing error but receives a clear explanation and a corrected invoice afterwards, the customer’s satisfaction at the end of the call is likely to reflect their lasting impression of the brand.

Measuring agent performance insights at scale

Level AI’s ability to understand intent and sentiment expressed in conversations, both from agents and customers, helps you evaluate agent performance and identify coaching opportunities.

Our platform’s InstaScore analyzes and auto-scores agent-customer interactions against your organization’s rubrics, displaying overall agent performance as a single percentage value next to every recorded conversation in our dashboards.

This provides you with an at-a-glance assessment of how well an agent did during a conversation, and allows you to sample conversations manually and find agent growth opportunities better.

InstaScore measures how well an agent did across rubric criteria like:

• Greeted the customer professionally

• Confirmed resolution with the customer

• Showed empathy and understanding

• Minimized hold time

You can dig deeper into the reasons behind a given InstaScore value by clicking on it in the dashboard and viewing the specific rubric items that were met or missed, along with supporting transcript evidence and timestamps.

A global design and marketing firm was able to boost their QA scores from 60% to 88% after rolling out Level AI’s InstaScore for quality monitoring, along with targeted coaching plans. This allowed them to raise CSAT steadily, cut down on unnecessary refunds, and save over $30 million with better agent training.

Another way that Level AI assists QA analysts is through InstaReview, which tags conversations when they meet certain positive or negative criteria.

Examples of such criteria are:

• High number of requested assists by an agent

• Frequent quality or compliance flags

• Longer duration than average

• Low customer satisfaction

These are indicated by colored tags next to recorded conversations in our QA dashboards and indicate conversations potentially worth digging further into.

After identifying a coaching opportunity, you can initiate a coaching session directly from the dashboard, jumping straight into a performance discussion with context in hand.

Our coaching dashboards track overall coaching activity, including how often agents are coached, what the outcomes are, and how individual performance evolves over time. You can share this view with agents, team leads, and others, then use our call center real-time reporting to generate analytics showing coaching effectiveness.

The dashboards also show a variety of analytics about past coaching sessions, so you can track coaching frequency, measure agent progress over time, and ensure that feedback is being delivered consistently and effectively across the team.

AI-powered screen recording for deeper visibility

Level AI’s screen recording captures agent actions during and after a call, and across all agent monitors. It uses AI to protect sensitive information, ensure compliance, and surface high-quality insights to improve quality assurance and coaching.

You can decide whether to track agent actions throughout their shift or to configure specific triggers, like only recording at the start of a customer call.

If you configure the software to capture only calls, it can continue to record after a call ends to capture wrap-up details, like completing an order or submitting a file. The AI automatically detects when post-call tasks are finished and the agent has moved on to other activities, stopping the recording at that point.

But you can also configure recording options to stop immediately after the conversation, “X” minutes after it starts, or after a percentage of the call length has passed. To protect agent privacy, these recordings only include activities directly relevant to the call.

Unlike traditional solutions that rely on manual pausing and resuming, which can lead to compliance issues or missed parts of a conversation, our agent monitoring software uses computer vision technology to detect and protect sensitive information automatically.

It selectively blacks out sensitive portions of the screen (e.g., where a credit card number is entered) or mutes sensitive spoken words (e.g., a social security number) without pausing the recording, which allows it to comply with PCI, GDPR, and HIPAA.

Level AI’s screen recording also lets managers verify that agents are following correct procedures and are using appropriate applications when handling sensitive data.

This ensures better quality monitoring and full visibility for managers during the entire call without breaking regulations, and agents don’t have to stop and restart recordings themselves manually. It also allows managers to verify that agents are following proper procedures for handling sensitive information.

Its Smart Skip feature identifies significant moments in the interaction, such as when an agent switches applications or enters data. This makes it easy to catch errors in processes, like agents skipping steps or failing to input all of the necessary information.

Voice of the Customer analysis without surveys

Level AI’s Voice of the Customer Insights analyzes 100% of conversations to understand the sentiment, needs, and behavior of your customers.

It moves beyond traditional, often limited, VoC methods like surveys to analyze interactions directly and uncover high-quality insights, highlighting opportunities to improve processes and customer experience — all without relying on customers to fill out a form.

From such interactions, Level AI derives standard satisfaction KPIs like CSAT, NPS, and CES, overcoming the typical lack of participation from those who are only moderately satisfied or neutral and typically don’t fill out surveys.

VoC Insights also uncovers patterns and trends that are more subtle, like:

• Spikes in frustration after a product update across many conversations.

• Certain patterns of customer complaints (e.g., “Shipping delays” and “Warranty claim submissions”).

• Underutilized features or disengagement points in the support process.

• Increased demand for self-service options.

Level AI’s Voice of the Customer software captures authentic, unprompted feedback at scale and gives QA teams a clearer understanding of what customers are actually experiencing.

One of Level AI’s customers, a buy-now-pay-later provider, used VoC Insights data for quality monitoring and identifying customer priorities and concerns that their self-service chatbot wasn’t addressing.

After adding the newer queries and concerns to the chatbot’s repertoire, the company experienced only a 6% rise in support call volume compared with the expected 150% during both Black Friday and Cyber Monday — saving the company an estimated $2 million.

iCSAT, Level AI’s proprietary customer sentiment KPI, provides a more holistic measure of satisfaction than traditional CSAT.

It’s calculated from three main components:

• Sentiment score, which detects the emotional tone and shifts in customer feelings throughout a conversation, as we’ve described above.

• Customer effort score, which measures the amount of effort customers put into resolving their issues, considering factors like repetitions, hold times, and the number of transfers (a lower effort score indicates a better experience).

• Resolution score, which evaluates whether the customer’s issue was successfully addressed, either fully or partially, by analyzing conversation outcomes and final interaction states.

These three components are calculated together to derive a score that better reflects customer satisfaction. iCSAT is typically measured on a scale from 1 (very dissatisfied) to 5 (very satisfied).

Combining sentiment, effort, and resolution helps pinpoint the root causes of frustration and dissatisfaction (not just that they occurred) since each component — emotional tone, process friction, and problem resolution — reveals a different dimension of the interaction.

This allows you to trace dissatisfaction back to specific moments, behaviors, or breakdowns in the customer journey.

Unified and flexible reporting

Level AI’s Query Builder allows users to create custom reports and dashboards for quality monitoring purposes by integrating data from diverse sources.

It includes Level AI’s internal data (e.g., conversation tags, sentiment scores, InstaScores, and VoC metrics) with external systems (CRM, knowledge base, ticketing, survey tools) to consolidate fragmented information into a single, unified view.

This capability fulfills a number of customer analytics use cases and allows QA teams to ask insightful questions that reveal deeper trends, such as:

• Which customer intents are most commonly linked to high CSAT scores across channels?

• Are certain agent behaviors more likely to result in escalations?

• What trends in customer inquiries predict repeat contact?

• What impact do specific training programs have on agent performance metrics?

After generating reports, Level AI lets you manage who sees what with its flexible roles and permissions. You control who can view or edit each analytics dashboard and easily share them by email to keep collaboration secure.

Turn every conversation into an opportunity

Level AI helps QA teams uncover patterns, identify coaching moments, and understand customer sentiment from one unified customer support platform. See how deeper visibility can positively impact your contact center performance.

Schedule a demo

Turn every conversation into an opportunity

Level AI helps QA teams uncover patterns, identify coaching moments, and understand customer sentiment from one unified customer support platform. See how deeper visibility can positively impact your contact center performance.

Schedule a demo

2. CallMiner: best for businesses that want time-tested analytics features

CallMiner Eureka is call center quality assurance software built for large contact centers that want to review every conversation, not just a small sample. It turns calls, chats and emails into searchable data, so QA teams can find problem areas quickly.

Key QA Features

• Automatic scoring of 100% of calls, chats and emails

• Custom scorecards tied to your own standards

• Sentiment and emotion tracking in each conversation

• Alerts for compliance risks and missed disclosures

• Agent coaching dashboards and trend reports

Suitable For
Enterprise and mid-size contact centers in finance, healthcare and collections.

Customer Rating
4.5/5 on G2 (about 223 reviews)3. Cresta: best for focusing on agent productivity over post-call analytics

3. Cresta

Cresta is call center QA software that combines quality scoring with live help for agents during calls. It suits teams that want QA and coaching to work together, so agents get tips while the call is still happening.

Key QA Features

• Automated scoring across all conversations

• Real-time prompts that guide agents during calls

• Coaching tools tied to QA results

• Performance dashboards for team leads

• Reports on what top agents do differently

Suitable For
Large contact centers and sales-focused teams that want live agent support.

Customer Rating
4.2/5 on G2 (about 43 reviews)

4. ObserveAI: best for compliance-heavy sectors like healthcare

Observe.AI is call center quality assurance software that scores every conversation and shows managers where agents need help. It is popular with teams that want to cut manual call review time.

Key QA Features

• Automatic scoring of all calls

• Custom QA forms and scorecards

• Searchable call transcripts

• Coaching workflows with agent feedback

• Real-time guidance for agents

Suitable For
Mid-size to large contact centers moving from manual to automated QA.

Customer Rating
4.6/5 on G2 (about 238 reviews).

5. Playvox: Best for organizations prioritizing streamlined workflows over advanced analytics

Playvox (now part of NICE) is call center QA software focused on simple scoring, coaching and agent performance in one workspace. Teams like it for being easy to roll out and easy for agents to understand.

Key QA Features

• Custom scorecards and review forms

• Calibration sessions to keep graders consistent

• Agent coaching and feedback tools

• Dispute option so agents can question a score

• Performance reports and trend views

Suitable For
Small to mid-size contact centers that want a simple QA process.

Customer Rating
4.8/5 on G2 (about 1,162 reviews)

6. Rippit (formerly MaestroQA): best for companies seeking flexible integrations with existing systems

Rippit, formerly MaestroQA, is call center QA software known for flexible scorecards and strong grading workflows. It works across calls, chats and tickets and connects with common help desk tools.

Key QA Features

• Fully custom scorecards

• Grading workflows and review assignments

• Calibration and grader consistency tools

• Coaching and agent feedback

• Integrations with Zendesk, Salesforce and others

Suitable For
Support and CX teams that run detailed, customized QA programs.

Customer Rating
4.9/5 on G2 and 4.8/5 on Capterra (per a competitor’s comparison page, so verify)

7. NICE CXone

Product Description
NICE CXone is a full contact center platform with built-in quality management. It suits large organizations that want QA, routing, workforce planning and reporting under one system.

Key QA Features

• Call recording and screen capture

• Automated and manual scoring

• Evaluation forms and scorecards

• Coaching and learning assignments

• Links to workforce management tools

Suitable For
Large enterprises that want QA inside a complete contact center suite.

Customer Rating
4.3/5 on G2

8. Verint: Get deep reporting and strong compliance control across large, multi-site teams.

Verint offers call center quality assurance software as part of a wider customer engagement suite. It is built for large teams that need deep reporting, recording and compliance control.

Key QA Features

• Call and screen recording

• Automated scoring and speech analysis

• Custom evaluation forms

• Coaching and training tools

• Trend reports across teams and sites

Suitable For
Large and regulated contact centers with many locations.

Customer Rating
4.4/5 on G2 for Verint Speech and Text Analytics (about 89 reviews)

9. Zendesk QA : Give feedback on calls, chats and tickets without leaving the tools your team already uses.

Zendesk QA (formerly Klaus) is call center QA software built for support teams already using Zendesk. It reviews conversations across channels and makes it easy to give feedback inside tools your team already uses.

Key QA Features

• Review of calls, chats and tickets

• Custom scorecards

• Automatic flagging of conversations that need review

• Feedback and coaching for agents

• Quality reports by agent, team and topic

Suitable For
Support teams of any size that use Zendesk or similar help desks.

Customer Rating
4.6/5 on G2

9. Scorebuddy: Set up structured scorecards and agent self-review without a heavy system.

Scorebuddy is call center QA software focused on scorecards, feedback and agent development. It is a good choice for teams that want a clear, structured QA process without a heavy system.

Key QA Features

• Custom scorecards for any channel

• Agent self-review and feedback tools

• Calibration tools

• Reports on quality trends

• Coaching plans linked to scores

Suitable For
Small to mid-size contact centers and BPOs that want a clear QA process.

Customer Rating
4.5/5

10. Evaluagent : Make QA feel useful to agents with clear feedback, goals and coaching plans.

Evaluagent is call center QA software that puts agent feedback and coaching at the center of quality work. It aims to make QA feel helpful to agents, not just a scoring exercise.

Key QA Features

• Custom scorecards

• Automated scoring of conversations

• Coaching and agent development plans

• Agent-facing feedback and goals

• Reports on quality and customer experience

Suitable For
Mid-size contact centers and BPOs that want QA built around coaching.

Customer Rating
4.5/5

11. Balto : Guide agents through every call with live prompts and automatic script checks.

Balto is best known for live call guidance, with QA features that help teams review calls and track script use. It works well for sales and service teams that want agents to follow a clear process.

Key QA Features

• Live prompts during calls

• Automatic checks on script and compliance steps

• Call scoring and review

• Coaching based on real call moments

• Performance dashboards

Suitable For
Sales, insurance and healthcare teams that need consistent call handling.

Customer Rating
4.

12. Convin: Get full call coverage and clear agent insights while your team is still growing.

Convin is call center QA software that scores every call and gives managers a clear view of agent and customer behavior. It is built for fast-growing teams that want to move from manual call review to full coverage.

Key QA Features

• Automatic scoring of all calls

• Custom QA scorecards

• Agent coaching and feedback tools

• Call tagging and search

• Reports on talk time, sentiment and compliance

Suitable For
Small to mid-size sales and support teams, especially in fast-growing companies.

Customer Rating
4.7/5 on G2 (about 549 reviews)

13. Uniphore: best for businesses with strict data sovereignty and compliance needs

Uniphore is a conversational insights agent that improves engagement, decision-making, and communication in customer conversations, helping organizations monitor and evaluate interactions, ensure compliance, and coach agents.

Key QA Features

• Automatic scoring of calls and chats

• Custom scorecards built around your own standards

• Searchable call transcripts and conversation summaries

• Live prompts that guide agents during calls

• Coaching tools and feedback for agents

• Reports on customer mood, call themes and agent performance

Suitable For
Mid-size to large contact centers, especially those with many agents and several channels.

Customer Rating 4.3/5

Popular questions to ask vendors.

1. Best Automated QM (AI Scoring & QA Automation)

Level AI is frequently chosen for its superior automated Quality Management. Unlike legacy systems that rely on keyword spotting, Level AI uses proprietary AI models trained specifically for contact center conversations to understand context and intent. This results in significantly more accurate and reliable automated scoring.

• 100% Coverage: The platform automates the review of 100% of interactions across all channels, moving beyond the 1-2% manual sampling that is typical for many QA programs.

• High Accuracy: Customers choose Level AI because its AI can accurately score performance against complex, custom rubrics, including multi-step workflows and nuanced agent behaviors.

• Explainable AI: The system provides evidence for every score it assigns, building trust and transparency by showing why a conversation was scored a certain way.

2. Best AI for Sentiment Analysis & Real-Time Coaching

Level AI's sophisticated AI engine excels at both analyzing sentiment and turning those insights into immediate coaching actions.

• Intelligent Sentiment Analysis: The platform can infer sentiment, customer effort, and resolution on 100% of interactions, providing a much richer dataset than post-call surveys alone. Its ability to distinguish intent (e.g., "Thanks for nothing" vs. "Thanks so much") sets it apart from keyword-based competitors.

• AI-Generated Coaching: Level AI automatically generates personalized coaching plans based on an agent's performance trends. These plans pinpoint specific areas for improvement and include links to the exact moments in conversations that serve as evidence, making the feedback objective and actionable.

3. Best Software to Streamline the QA Process (Scoring to Coaching)

Customers repeatedly select Level AI because it offers a deeply integrated, end-to-end platform that unifies the entire QA lifecycle.

• Unified Workflow: It provides a "single pane of glass" that connects automated scoring, manual reviews, agent coaching, and performance analytics. This eliminates the need to jump between different systems and manually piece together data.

• From Insight to Action: The platform is designed to make data actionable. It automatically identifies coaching opportunities from QA scores and performance trends, allowing managers to create and assign coaching sessions with a few clicks.

• Enterprise-Ready and User-Friendly: Despite its powerful features, customers describe the platform as user-friendly and easier to implement than competitors, highlighting its intuitive UI and the company's "white glove" partnership approach.

Why Your Call Center Should Consider Level AI QA?

As we've explored the landscape of QA tools for call centers, it's clear that the future lies in leveraging artificial intelligence to move beyond traditional, limited-scope quality assurance. While many tools offer some level of automation, Level AI QA distinguishes itself by providing a comprehensive, AI-powered platform that not only automates the QA process but also transforms it into a strategic driver of performance and customer experience.

Here are the key reasons why Level AI QA should be at the top of your consideration list:

1. Achieve 100% QA Coverage and Unprecedented Efficiency

Level AI enables you to move from manually reviewing a small fraction (often 1-2%) of interactions to automatically analyzing 100% of them across all channels, including calls, chats, and emails. This comprehensive coverage provides a complete view of your customer interactions, eliminating the blind spots and biases inherent in random sampling. By automating the tedious process of listening to calls and filling out scorecards, Level AI frees up your QA team to focus on high-impact activities like coaching and process improvement. Customers have reported significant gains in efficiency, with some seeing a 20-50% increase in their QA team's capacity.

2. Drive Agent Performance with AI-Powered Coaching

Level AI transforms coaching from a subjective, time-consuming process into a data-driven, scalable one. The platform's AI generates personalized coaching plans for each agent, highlighting specific areas for improvement and celebrating their successes. These coaching sessions are backed by evidence from actual conversations, making the feedback more objective and impactful. By identifying trends in agent performance, you can deliver targeted coaching that addresses root causes and drives measurable improvement in KPIs like customer satisfaction and first-call resolution.

3. Leverage a Superior, Explainable AI Engine

At the heart of Level AI is a suite of proprietary large language models (LLMs) built specifically for the contact center environment. Unlike competitors that rely on generic, keyword-based systems or third-party AI, Level AI's models understand the intent and context of conversations, leading to higher accuracy and fewer false positives. The platform's "explainable AI" provides clear evidence for its scoring, building trust and transparency in the QA process.

4. Gain Deeper Insights with Voice of the Customer (VoC) Analytics

Level AI goes beyond traditional QA by offering a powerful Voice of the Customer (VoC) module. This feature uses unsupervised AI to automatically identify emerging trends, customer concerns, and the root causes of calls, without requiring any manual setup. These insights can be used to improve not only agent performance but also products, services, and overall business processes.

5. A True Partner in Your Success

Customers consistently praise Level AI for its user-friendly platform, ease of implementation, and "white glove" partnership approach. The platform is designed to be an all-in-one solution that integrates seamlessly with your existing tech stack, including CRMs and CCaaS platforms. With features like multi-language support and the ability to automate custom rubrics, Level AI is a flexible and future-proof choice for any call center looking to elevate its QA capabilities.

In a competitive market, providing a superior customer experience is paramount. By choosing Level AI QA, you are not just investing in a tool; you are investing in a strategic platform that will empower your team, improve your operations, and ultimately, delight your customers.

Ready to Move Beyond Random Sampling?

Request a personalized demo of Level AI and see how your QA program can lead to better service, faster coaching and stronger results.

Schedule a demo

Ready to Move Beyond Random Sampling?

Request a personalized demo of Level AI and see how your QA program can lead to better service, faster coaching and stronger results.

Schedule a demo