Software Buyer’s Guides

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

Updated:

November 2, 2026

Authored by

Richard James Director of Organic Growth and CX

Reviewed by

Sean Minter Founder, CEO

Call center quality assurance (QA) software evaluates customer interactions handled by live agents and AI agents, automates compliance scoring, and turns conversational data into coaching inputs and corrective actions. QA teams, team leaders, CX leaders, and teams managing AI agents use call center quality assurance software to monitor compliance, define coaching priorities, calibrate evaluator and AI scoring, and maintain documentation for QA audits.

AI agents are handling increasing amounts of customer contacts alongside live agents, changing what QA teams need to evaluate as customer interactions transfer between automated and live service. Gartner's latest research report calls for AI agents and live agents to be held to a shared customer outcome standard, with quality assurance evaluation methods adapted for automated service. CMP Research's Q3 Automated QA/QM Prism identified growing demand amongst customer service and experience leaders for QA of AI voice, chat, and text agents alongside live contacts, naming data integration among buyers' key investment criteria.

Our team of CX specialists and contact center leaders reviewed and evaluated 19 call center quality assurance software vendors, examining their data integrations, customer journey coverage, and ability to turn quality findings into corrective action and measured improvement.

From our research, we selected the five best call center quality assurance software providers of 2026.

• AmplifAI
• EvaluAgent
• Level AI
• Observe.AI
• SuccessKPI

The call center quality assurance software market is saturated with providers that are exceptional at transcribing customer interactions, scoring calls, identifying sentiment and root causes, and monitoring live agent compliance, with some vendors also scoring AI agent and live agent conversations separately, but not whether the customer's issue was resolved by the end of the customer journey.

With AI agents and self-service taking on more complex customer interactions, customer service and support teams need to connect quality assurance and compliance evaluations with AI-to-human handoff records, CRM case histories, customer surveys, transaction records, and contact center KPIs to evaluate one connected customer journey, giving QA teams the context to identify where service failed and route findings to the teams responsible for corrective action.

How We Evaluated Call Center Quality Assurance Software Vendors: We assessed data integrations by the contact center software and data sources vendors connect to, customer journey coverage by the stages their QA scores, and software types, compliance monitoring, and quality assurance features against documented, generally available capabilities.

Compare the Best Call Center Quality Assurance Software of 2026

Compare the best call center quality assurance software of 2026 by data sources vendors connect and customer journey stages their QA scores, including whether QA follows one customer through AI agent conversations, AI-to-human handoffs, and live agent interactions to outcomes after contact.

Leading Call Center Quality Assurance Software in 2026

Of the 19 call center quality assurance software providers researched, we selected five leading vendors based on their documented data integrations, customer journey coverage, and ability to turn quality findings into corrective action and measured improvement. Gartner's research on AI-driven service QA calls for AI agents and live agents to be accountable to shared customer outcomes, with quality findings driving targeted improvements.

• AmplifAI
• EvaluAgent
• Level AI
• Observe.AI
• SuccessKPI

Call Center Quality Assurance Software Integrations

Data integrations determine which customer and interaction records reach call center quality assurance software, while scoring capabilities determine what vendors evaluate from those records. CMP Research's 2026 Prism for Automated QA/QM identified data integration as one of the most significant challenges customer service and support leaders face with AI investments. Our research evaluated documented data integrations for 19 call center quality assurance software providers, including connections to CCaaS, AI agent platforms, CRM, survey, WFM, and other enterprise software.

Call Center Quality Assurance Software Must Evaluate the Full Customer Journey

Call center quality assurance software needs to connect AI agent conversations, handoffs, and live agent interactions with customer outcomes, so QA teams can evaluate service quality through the full customer journey. We’ve mapped four customer journey stages to show what QA needs to score and what call center quality assurance software misses when part of the journey goes unmeasured.

Types of Call Center Quality Assurance Software

Call center quality assurance software includes six overlapping types based on QA function, data available for AI evaluation, and deployment as independent software or part of a broader contact center suite. Start with how your contact center scores interactions, manages quality programs, and acts on quality findings, then compare vendors by QA functions, data access, and deployment model.

Real-Time vs Post-Call Compliance Monitoring

Real-time compliance monitoring identifies disclosure and policy risks during live calls and chats, alerting agents and supervisors in time to intervene before the interaction ends. Post-call compliance monitoring evaluates completed interactions for violations, documenting findings for investigation and audit. Compliance requirements apply to AI agent conversations as well as live agent interactions.

LLMs vs Call Center Quality Assurance Software

When comparing purpose-built AI-powered call center quality assurance software with general-purpose LLMs, including GPT, Claude, Gemini, and internally deployed AI models, you need to understand how both approaches process information and act on QA findings. An LLM can analyze transcripts, apply QA scorecards, and identify potential compliance issues, but a contact center QA program also requires connected interaction and customer data, scoring calibration, security controls, and workflows that turn findings into corrective action and measured improvement.

Call Center Quality Assurance Software Features

We’ve compiled the top call center quality assurance software features from our evaluation of 19 providers, grouping capabilities into Quality Intelligence, Corrective Action, and Measured Improvement based on what QA software analyzes, how findings reach the teams responsible for action, and whether vendors measure changes in agent performance, AI agent outcomes, and customer feedback.

Call Center Quality Assurance Software Evaluation Criteria

We used the following call center quality assurance software evaluation criteria to examine providers based on documented capabilities and enterprise fit. Use the evaluation framework below to test vendor claims against your interaction volumes, scorecard complexity, compliance requirements, current CCaaS, interaction data sources, and budget.

Call Center Quality Assurance Software Reviews (2026)

To identify the best call center quality assurance software, we reviewed 19 providers based on documented data integrations, customer journey coverage, and quality assurance capabilities. Reviews appear in alphabetical order, with specifications, best-fit use cases, and deployment considerations you can compare against your contact center requirements.

AmplifAI Call Center Quality Assurance Software

AmplifAI call center quality assurance software transcribes, summarizes, and scores 100% of customer interactions using a unified data foundation connecting 150+ data sources, including CCaaS, CRM, WFM, survey, and AI agent platforms. AmplifAI connects AI agent conversations, AI-to-human handoffs, live agent conversations, and post-contact outcomes into one customer journey for quality evaluation, routing findings into corrective actions for QA teams, team leaders, and teams managing AI agents.

Gartner's September 2026 report, How Service QA Should Evaluate AI-Driven Customer Interactions, features AmplifAI's customer journey evaluation, and CMP Research's Q3 2026 Prism for Automated QA/QM names AmplifAI a Leading provider with the highest possible Integration score.

AmplifAI Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use AmplifAI

• Mid-market and enterprise contact centers and BPOs needing QA built on unified data to evaluate AI agent conversations, AI-to-human handoffs, live agent interactions, and customer outcomes as one journey.
• Contact centers with interaction, CRM, WFM, and survey data split among separate software.
• Enterprise QA teams analyzing customer sentiment, contact reasons, recurring service issues, and root causes across interaction and customer data.
• Contact centers moving from sampled manual QA to 100% automated interaction scoring, with configurable scorecards, calibration, compliance monitoring, and AI scoring accuracy tracking.
• QA teams routing quality findings into assigned coaching, next best actions, agent recognition, and AI agent corrections, with follow-through across team leaders and AI agent teams.
• Contact centers connecting QA scores with CSAT, NPS, and performance data to measure coaching effectiveness, compliance adherence, and improvements in customer outcomes.
• BPOs managing quality by client, site, queue, or program.

AmplifAI Considerations

• Contact centers with fewer than 20 agents should assess whether their QA programs require the breadth of AmplifAI's unified quality assurance and performance management capabilities.
• Contact centers requiring in-call agent prompts and real-time compliance guidance need a separate real-time agent assist (RTAA) provider alongside AmplifAI.
• Contact centers retain their communications infrastructure when connecting AmplifAI to existing CCaaS, telephony, and routing software.
• Onboarding includes calibrating AI-generated QA scores against existing quality standards and human evaluator results.

Speak With a CX Leader at AmplifAI About Your QA Program

Balto Call Center Quality Assurance Software

Balto call center quality assurance software monitors live calls against playbooks and checklists, prompting agents with script guidance and compliance alerts in real time. Balto pairs real-time guidance with Auto QA scoring of completed calls, drawing call audio from CCaaS software and centering evaluation on live agent conversations.

Balto Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Balto

• Sales and outbound contact centers guiding agents through scripted calls in real time.
• Service teams needing in-call script adherence and compliance prompts on voice calls.
• Contact centers on Five9, Genesys Cloud, NICE CXone, Talkdesk, or other CCaaS software Balto integrates with.

Balto Considerations

• Contact centers deploying AI agents need separate QA for AI agent conversations and AI-to-human handoffs, as Balto scores live agent calls.
• Contact centers requiring survey, WFM, and business data in their QA evaluations should review Balto's documented integration coverage, which centers on CCaaS call audio.

Compare Balto to AmplifAI for Call Center Quality Assurance Software

CallMiner Call Center Quality Assurance Software

CallMiner call center quality assurance software analyzes recorded calls and digital interactions, scoring conversations through configurable analytics categories and flagging compliance risks for review. CallMiner's evaluation centers on live agent conversations, with survey integrations connecting customer feedback to interaction scores.

CallMiner Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use CallMiner

• Enterprise contact centers using configurable speech and text analytics to evaluate quality and monitor compliance across high volumes of customer interactions.
• Contact centers with dedicated analyst teams configuring and maintaining analytics categories.
• Regulated contact centers prioritizing compliance monitoring on calls and digital interactions.

CallMiner Considerations

• Contact centers without an analytics team should plan for the analyst time CallMiner's category building and tuning requires.
• Contact centers deploying AI agents need separate evaluation for AI agent conversations and AI-to-human handoffs alongside CallMiner.

Compare CallMiner to AmplifAI for Call Center Quality Assurance Software

Convin Call Center Quality Assurance Software

Convin call center quality assurance software scores calls against configurable QA scorecards using AI-powered conversation analysis, while providing real-time prompts to live agents. Convin evaluates live agent conversations and conversations handled by its AI voicebot, with helpdesk, CRM, and survey integrations adding customer context to interaction scores.

Convin Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Convin

• Small to mid-sized contact centers moving from manual QA to automated call scoring with real-time agent prompts.
• Contact centers using Convin's AI voicebot and scoring voicebot and live agent conversations in one QA program.

Convin Considerations

• Contact centers using third-party AI agents or requiring QA scoring of AI-to-human handoffs should evaluate those requirements separately from Convin's native voicebot and live agent QA.
• WFM schedules and ERP records sit outside Convin's documented integrations.

Compare Convin to AmplifAI for Call Center Quality Assurance Software

Cresta Call Center Quality Assurance Software

Cresta call center quality assurance software scores customer conversations for compliance, process adherence, and outcome behaviors, paired with real-time agent guidance during live calls and chats. Cresta applies a shared quality framework to live agent conversations and conversations handled by AI agents built in Cresta, inferring outcomes such as resolution and CSAT from the conversation itself.

Cresta Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Cresta

• Sales and service contact centers pairing automated QA scoring with real-time guidance during live conversations.
• Contact centers deploying only Cresta's AI agents and applying shared quality standards to AI agent and live agent interactions inside Cresta.
• Enterprise QM teams managing hybrid evaluation, with AI scoring interactions and evaluators handling calibration and appeals.

Cresta Considerations

• Contact centers comparing QA scores with survey results should account for Cresta inferring resolution and CSAT from conversations, with survey data outside its documented integrations.
• Contact centers requiring QA scoring of AI-to-human handoffs should evaluate that requirement separately, as Cresta tracks escalations and carries context through handoffs without scoring the transfer.

Compare Cresta to AmplifAI for Call Center Quality Assurance Software

Dialpad Call Center Quality Assurance Software

Dialpad call center quality assurance software grades Dialpad Contact Center calls against AI scorecards, with real-time agent assist prompting agents during live conversations. Dialpad's QA covers interactions handled inside Dialpad, with resolution and AI CSAT analytics for Dialpad AI agents and post-call CSAT surveys tied to individual calls.

Dialpad Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Dialpad

• Contact centers using Dialpad Contact Center for calling and messaging that want automated scoring inside their existing deployment.
• Small and mid-sized teams grading calls with AI scorecards and sharing grades with agents.
• Teams using Dialpad AI agents and tracking resolution and AI CSAT per AI agent.

Dialpad Considerations

• Dialpad's QA scores conversations handled in Dialpad, so contact centers using other CCaaS providers need separate QA for those interactions.
• Dialpad grades live agent calls against AI scorecards, while its AI agent analytics measure resolution, deflection, and AI CSAT rather than scoring AI agent conversations against those QA criteria.
• CRM, WFM, and third-party survey data sit outside Dialpad's documented QA integrations.

Compare Dialpad to AmplifAI for Call Center Quality Assurance Software

Enthu.AI Call Center Quality Assurance Software

Enthu.AI call center quality assurance software scores calls against configurable QA criteria, keywords, and sentiment cues, keeping manual review alongside automated scoring. Enthu.AI evaluates live agent conversations, drawing calls from CCaaS software and connecting helpdesk and CRM records to interaction scores.

Enthu.AI Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Enthu.AI

• Small to mid-sized contact centers with lean QA teams automating manual call evaluations.
• Teams needing calibration and coaching workflows alongside automated call scoring.
• Contact centers connecting automated call evaluations with customer records in Zendesk, Freshdesk, Salesforce, or HubSpot.

Enthu.AI Considerations

• Enthu.AI's QA covers live agent calls, with AI agent conversations and customer outcomes after contact outside its evaluation.
• Contact centers measuring QA against survey results or WFM data need connections beyond Enthu.AI's documented integrations.

EvaluAgent Call Center Quality Assurance Software

EvaluAgent call center quality assurance software pairs automated interaction scoring and quality management, using calibration and Auto QA accuracy tracking to keep AI scores in line with human evaluators. EvaluAgent evaluates live agent conversations and AI agent conversations from connected AI agent platforms, and its repeat contact detection flags customers contacting again about an unresolved issue.

EvaluAgent Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use EvaluAgent

• Contact centers and BPOs pairing automated QA with structured quality management, including calibration, disputes, and AI scoring accuracy checks.
• Contact centers evaluating AI agents from connected AI agent platforms alongside live agents.
• Teams connecting Zendesk tickets and survey results to QA, with helpdesk integrations extending to Freshdesk, Intercom, and Kustomer.

EvaluAgent Considerations

• Contact centers requiring AI-to-human handoff QA should assess whether EvaluAgent scores the transfer itself, including context passed and customer repetition, alongside its AI agent and live agent evaluations.
• Survey results reach EvaluAgent through Zendesk, with standalone survey software outside its documented integrations.

Compare EvaluAgent to AmplifAI for Call Center Quality Assurance Software

Genesys Call Center Quality Assurance Software

Genesys call center quality assurance software evaluates interactions handled in Genesys Cloud CX through AI scoring and configurable evaluation forms, with in-call compliance reminders guiding agents during live interactions. Genesys connects post-interaction survey responses to interaction quality records, filterable by agent, queue, and wrap-up code.

Genesys Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Genesys

• Contact centers using Genesys Cloud CX that want quality management and evaluation forms inside their existing deployment.
• Customer service teams guiding agents with in-call compliance reminders and knowledge.
• Genesys Cloud CX teams comparing post-call CSAT survey responses with interaction quality scores by agent, queue, and wrap-up code.

Genesys Considerations

• Genesys quality management evaluates interactions routed and recorded in Genesys Cloud CX, with interactions from other CCaaS providers outside its QA coverage.
• Genesys reports virtual agent containment, transfer, and escalation rates without scoring virtual agent conversations or AI-to-human handoffs against QA criteria.

Compare Genesys to AmplifAI for Call Center Quality Assurance Software

Level AI Call Center Quality Assurance Software

Level AI call center quality assurance software scores customer interactions automatically, classifying conversations by topic and sentiment and flagging quality and policy violations for evaluator review. Level AI evaluates live agent and virtual agent conversations against shared QA rubrics and scores the timing of virtual agent escalations.

Level AI Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Level AI

• Contact centers scoring virtual agents built on Google Dialogflow, Amazon Lex, or Microsoft Copilot alongside live agents.
• Support teams on helpdesk software connecting tickets and conversations to QA.

Level AI Considerations

• Level AI scores when a virtual agent escalates to a live agent, while context passed at the handoff and customer repetition sit outside its scoring.
• QA findings reach coaching and follow-up through additional software, as Level AI's documented corrective actions center on real-time compliance alerts and CX trend alerts.

Compare Level AI to AmplifAI for Call Center Quality Assurance Software

NICE CXone Call Center Quality Assurance Software

NICE CXone call center quality assurance software evaluates interactions captured through CXone recording and routing with evaluation forms and AI scoring, with calibration aligning evaluator and automated results. NICE CXone attaches post-interaction CSAT survey scores to all segments of a contact and imports voice and screen recordings from Amazon Connect, Avaya, Cisco, and Genesys environments for quality management.

NICE CXone Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use NICE CXone

• Contact centers using NICE CXone that want quality management, WFM, and analytics inside the CXone suite.
• Enterprises recording on Amazon Connect, Avaya, Cisco, or Genesys and evaluating those recordings in CXone quality management.
• Teams prioritizing compliance, documentation, and structured evaluation workflows.

NICE CXone Considerations

• NICE reports AI agent goal completion and intent scores in dashboards, while QA evaluation of AI agent conversations sits outside documented CXone quality management.
• Contact centers requiring AI-to-human handoff QA should assess how NICE CXone evaluates context retention and customer repetition during transfers, as its documented handoff metrics count escalations rather than score transfer quality.

Compare NICE CXone to AmplifAI for Call Center Quality Assurance Software

Observe.AI Call Center Quality Assurance Software

Observe.AI call center quality assurance software scores transcribed calls and digital interactions against evaluation criteria, flagging behaviors and compliance moments for evaluator review. Observe.AI evaluates live agent conversations and conversations handled by Observe.AI's AI agents, with case management linking calls, chats, and emails about an issue into a continuous case record.

Observe.AI Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Observe.AI

• Contact centers scaling automated QA coverage of voice and digital interactions with conversation analytics and calibration.
• Teams using Observe.AI's AI agents and scoring AI agent conversations with scorecards configured during the AI agent build.
• Support teams following an issue through calls, chats, and emails in a continuous case record.

Observe.AI Considerations

• Observe.AI's AI agent QA covers conversations handled by AI agents built in Observe.AI, while contact centers using third-party AI agents need separate QA evaluation.
• Contact centers comparing QA scores with external CSAT survey results or WFM schedules need additional data analysis outside Observe.AI's documented QA integrations.

Compare Observe.AI to AmplifAI for Call Center Quality Assurance Software

OttoQA Call Center Quality Assurance Software

OttoQA call center quality assurance software scores live agent conversations against QA criteria, with interaction analytics and AI-generated coaching plans built from scored calls. OttoQA takes in uploaded call recordings and help desk exports, a file-based intake that skips CCaaS and CRM integration setup.

OttoQA Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use OttoQA

• Small contact centers starting automated QA from existing call recordings and help desk exports.
• QA teams using automated call scores to generate coaching plans from recorded agent conversations.

OttoQA Considerations

• OttoQA's file-based intake ties QA coverage to how often your team uploads recordings and exports.
• AI agent conversations, AI-to-human handoffs, and post-contact outcomes sit outside OttoQA's evaluation of live agent calls.

Compare OttoQA to AmplifAI for Call Center Quality Assurance Software

Rippit Call Center Quality Assurance Software

Rippit call center quality assurance software, formerly MaestroQA, scores interactions against custom scorecards through grading queues and calibration workflows, with automated scoring alongside manual review. Rippit evaluates live agent and AI agent conversations and predicts customer satisfaction from interaction data.

Rippit Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Rippit

• MaestroQA customers continuing custom scorecard and calibration programs under Rippit.
• QA teams with dedicated analysts managing structured evaluation programs and controlling scoring logic.

Rippit Considerations

• Rippit renamed itself from MaestroQA in February 2026 and describes itself as no longer a QA company.
• Rippit predicts customer satisfaction from interaction data rather than correlating survey responses with agent performance.

Compare Rippit to AmplifAI for Call Center Quality Assurance Software

ScorebuddyCX Call Center Quality Assurance Software

ScorebuddyCX call center quality assurance software scores interactions against custom scorecards through automated and manual evaluation, managing calibration and QA reporting for quality programs. ScorebuddyCX evaluates live agent conversations and AI chat and voice bot conversations for accuracy, tone, and compliance, attaching CSAT, NPS, and CES results from Zendesk and Genesys to evaluated interactions.

ScorebuddyCX Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use ScorebuddyCX

• Contact centers and BPOs building custom QA scorecards and calibration programs for live agents and AI bots.
• Support teams on Zendesk, Genesys, or Intercom selecting interactions for QA by CSAT, NPS, or conversation rating.

ScorebuddyCX Considerations

• QA findings reach agents through ScorebuddyCX's coaching workflows, with role-based routing to team leaders and real-time alerts outside its documented features.
• Contact centers using standalone survey software should assess how CSAT, NPS, and CES results reach ScorebuddyCX, as its documented survey connections are through Zendesk, Genesys, and Intercom.

Compare ScorebuddyCX to AmplifAI for Call Center Quality Assurance Software

SuccessKPI Call Center Quality Assurance Software

SuccessKPI call center quality assurance software pairs speech and text analytics, automated scoring, and quality management with real-time agent assist during live interactions. SuccessKPI applies evaluation forms and scorecards to live agent and AI agent transcripts and connects survey results and BI reporting to quality scores.

SuccessKPI Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use SuccessKPI

• Contact centers evaluating live agents and third-party AI agent conversations against shared QA scorecards.
• Contact centers pairing post-call QA with real-time agent assist and compliance alerts.
• Teams tracking compliance adherence and Auto QA accuracy against human evaluators over time.

SuccessKPI Considerations

• Handoff scoring, including context passed and customer repetition, sits outside SuccessKPI's documented AI agent QA.
• SuccessKPI measures compliance adherence and Auto QA accuracy over time, while tracking whether coaching changed agent performance sits outside its documented features.

Compare SuccessKPI to AmplifAI for Call Center Quality Assurance Software

Talkdesk Call Center Quality Assurance Software

Talkdesk call center quality assurance software scores recorded interactions with evaluation forms, sentiment analysis, and screen capture built into the Talkdesk suite. Talkdesk connects post-contact CSAT and NPS surveys to individual interactions, including conversations handled only by Talkdesk AI agents.

Talkdesk Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Talkdesk

• Contact centers using Talkdesk for routing and WFM that want QA inside their existing Talkdesk deployment.
• Teams reviewing calls with screen recording alongside audio for QA and compliance.
• Talkdesk customers collecting post-contact CSAT and NPS through IVR, SMS, chat, and web surveys.

Talkdesk Considerations

• Talkdesk's QA depends on Talkdesk recording, keeping interactions from other CCaaS providers out of its evaluations.
• Talkdesk's quality scoring for AI agents is in preview for select customers, while AI agent sessions in general release report transcripts, sentiment, and escalation rates.

Compare Talkdesk to AmplifAI for Call Center Quality Assurance Software

Verint Call Center Quality Assurance Software

Verint call center quality assurance software scores interactions with automated and evaluator-led quality management inside its workforce engagement management (WEM) suite, alongside WFM and in-call guidance. Verint captures interactions from CCaaS providers including Amazon Connect, Avaya, Cisco, Five9, and Genesys, and connects Qualtrics and SurveyMonkey survey results to quality scores.

Verint Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Verint

• Enterprise contact centers using Verint WEM for quality management, workforce scheduling, and analytics.
• Enterprises evaluating interactions recorded on Amazon Connect, Avaya, Cisco, Five9, and Genesys through Verint quality management.
• Quality and compliance teams routing evaluation findings into coaching and recognition.

Verint Considerations

• Verint quality management is resold through Five9, so Five9 customers should confirm contract ownership, support responsibilities, and which vendor controls the QA product roadmap before purchasing.
• AI agent conversations and AI-to-human handoffs sit outside Verint's documented quality management, which centers on live agent interactions.

Compare Verint to AmplifAI for Call Center Quality Assurance Software

Zendesk QA Call Center Quality Assurance Software

Zendesk QA call center quality assurance software scores support conversations against custom scorecards through autoscoring and reviewer evaluations, built into the Zendesk suite. Zendesk QA reviews Zendesk AI agents and other bots on human agent scorecards, charting quality and CSAT survey results together by agent.

Zendesk QA Call Center Quality Assurance Software Specifications

Best Fit: Who Should Use Zendesk QA

• Support teams using Zendesk that want QA scorecards and autoscoring inside their existing Zendesk deployment.
• Teams scoring Zendesk AI agents and other bots alongside human agents.
• Zendesk support teams bringing conversations from Front or Gorgias into their QA programs.

Zendesk QA Considerations

• Zendesk QA's scoring depends on a connection to the Zendesk helpdesk, so contact centers on other helpdesk or CCaaS software should confirm coverage before purchasing.
• Voice QA covers calls from Amazon Connect and Five9, with other CCaaS providers outside Zendesk QA's documented integrations.

Compare Zendesk QA to AmplifAI for Call Center Quality Assurance Software

How to Evaluate Call Center Quality Assurance Software

Evaluating call center quality assurance software starts with understanding how your contact center is currently scoring customer interactions, where interaction, survey, CRM, and performance data resides, and which teams are responsible for acting on quality findings. From there, test whether a vendor's AI QA connects customer interactions through the full journey, supports corrective action, and measures improvements in service quality and customer outcomes. Use the steps below as a guide when you're reviewing call center quality assurance software vendors.

1. Define the problem QA needs to solve. Document where sampling misses interactions, AI agent conversations go unscored, handoffs lose customer context, evaluator and AI scores drift without calibration, or quality findings stop before coaching and follow-up. Set measurable targets for scoring coverage, calibration variance, compliance detection, and customer outcomes.
2. Check your stack. Use Check Your Stack to find your CCaaS, AI agent platforms, CRM, survey, WFM, and home-grown software, then confirm which vendors connect to your software.
3. Map your customer journey. Use the customer journey stages to record which stages your QA covers today and whether QA connects a customer's AI agent conversation, handoff, live agent conversation, and outcome after contact.
4. Choose your software type and compliance monitoring. Use the Types of Call Center Quality Assurance Software to compare types by the interaction and customer data they analyze, and Real-Time vs Post-Call Compliance Monitoring to decide whether you need alerts during live interactions, review of completed interactions, or both.
5. Test vendors with your data. Set requirements from the Call Center Quality Assurance Software Features, then use the Call Center Quality Assurance Software Evaluation Criteria throughout discovery, demonstrations, data assessments, and proofs of concept. Test vendors with representative AI agent conversations, handoffs, live agent recordings, CRM records, and customer survey results, comparing data integration and customer journey coverage alongside scoring accuracy, calibration, compliance detection, implementation effort, and cost.
6. Plan for measured outcomes. Confirm which roles receive quality findings, including QA teams, team leaders, and teams managing AI agents, and how corrective actions are assigned and followed through. Measure whether quality, compliance, and customer outcomes improve after corrective action for live agents and AI agents.

Read AmplifAI's guide to the best call center performance management software to compare vendors that connect QA findings with contact-center-wide performance workflows and measurement.

If you need support comparing call center quality assurance software vendors, speak to a CX leader at AmplifAI.

Speak to a CX Leader at AmplifAI

Customer Service and Support Software Buyer's Guides

Our CX specialists at AmplifAI research and evaluate customer service and support software for CX leaders, QA teams, compliance leaders, frontline leaders, and contact center decision-makers. AmplifAI's buyer's guides show you how vendors compare on software types, category features, best-fit use cases, and considerations, with evaluation criteria you can use when developing your shortlist.