# EvaluAgent vs Zendesk QA: which do AI models recommend for Contact center QA, October 2026

GTM AI Recommendation Index, October 2026 Edition, Contact center quality assurance. Six of fourteen models named EvaluAgent first on the direct prompt; two named Zendesk QA. Page: https://gtm-ai-index.com/customer/contact-center-quality-assurance/evaluagent-vs-zendesk-qa/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| EvaluAgent | 28% | #1 of 13 | 4% | 45 | 14 of 14 |
| Zendesk QA | 14% | #3 of 13 | 4% | 28 | 13 of 14 |

## The direct prompt, model by model

- Grok 4.1 Fast: evaluagent first (first choices: EvaluAgent, Scorebuddy) (alternatives: Balto, Talkdesk QM, Zendesk QA)
- Mistral Small: evaluagent first (first choices: EvaluAgent, Scorebuddy) (alternatives: Talkdesk)
- DeepSeek V4 Flash: evaluagent first (first choices: EvaluAgent) (alternatives: AmplifAI, Observe.AI, Scorebuddy, Talkdesk, Zendesk QA)
- Llama 4 Maverick: evaluagent first (first choices: EvaluAgent) (alternatives: GetApp, Scorebuddy)
- Kimi K2: evaluagent first (first choices: EvaluAgent) (alternatives: Playvox, ScorebuddyCX, Zendesk QA)
- GPT-6 Luna: evaluagent first (first choices: EvaluAgent) (alternatives: CallMiner Eureka, NICE CXone Quality Management)
- Gemini 3.5 Flash: zendesk qa first (first choices: Zendesk QA) (alternatives: EvaluAgent, Level AI, MaestroQA)
- Muse Glimmer 30B: zendesk qa first (first choices: Observe.AI, Zendesk QA) (alternatives: EvaluAgent, Playvox, Scorebuddy)
- Claude Haiku 4.5: neither first, one named (first choices: Scorebuddy) (alternatives: Convin, EvaluAgent, Gong, Level AI)
- GPT-5.4 mini: neither first, one named (first choices: Level AI) (alternatives: Calabrio ONE, Scorebuddy, Zendesk QA)
- Perplexity Sonar: neither first, one named (first choices: Scorebuddy) (alternatives: AmplifAI, Balto, EvaluAgent, Level AI)
- GLM 4.7 FlashX: neither first, one named (first choices: AmplifAI, Balto) (alternatives: EvaluAgent, Playvox QM, Scorebuddy)
- MiniMax M2.5: neither first, one named (first choices: Scorebuddy) (alternatives: EvaluAgent, Voxjar, Zendesk QA)
- Qwen 3.7 Flash: neither named (first choices: CallMiner Eureka) (alternatives: Five9 Agent Connect, MaestroQA, NICE CXone Quality Management, Playvox)

## What the models said about EvaluAgent

- "Users report repeated friction integrating with platforms like Amazon Connect, despite vendor instructions" (DeepSeek V4 Flash, negative prompt, soft negative)
- "limited dashboard customization for evaluagent" (GPT-6 Luna, negative prompt, soft negative)
- "For most companies with limited budgets, EvaluAgent at $35 per user offers the best balance of affordability and functionality." (Claude Haiku 4.5, budget prompt, first choice)
- "My default pick: evaluagent—if you already have a contact-center platform and want to add QA without replacing it." (GPT-6 Luna, direct prompt, first choice)
- "EvaluAgent: A mid-market blended AI + human QA platform with autoQM, conversation intelligence, and scorecard builder." (Llama 4 Maverick, paraphrase prompt, first choice)

## What the models said about Zendesk QA

- "Tools that rely heavily on AI scoring (e.g., Observe.AI, Kaizo, Zendesk QA/Formerly Klaus)" (DeepSeek V4 Flash, negative prompt, soft negative)
- "If you are Zendesk-native: Zendesk QA, formerly Klaus ... Zendesk QA gives the deepest native integration and risk-based review without manual sampling." (Muse Glimmer 30B, direct prompt, first choice)
- "A highly automated, AI-driven QA tool built specifically for support teams, now natively unified inside the Zendesk ecosystem." (Gemini 3.5 Flash, comparative prompt, first choice)
- "I'd recommend Zendesk QA (formerly Klaus) if your priority is support quality assurance and conversation review" (Perplexity Sonar, paraphrase prompt, first choice)

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.