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Contact center quality assurance · November 2026 Edition

EvaluAgent vs Insightful

Two of fourteen models named EvaluAgent first on the direct prompt; one named Insightful. EvaluAgent was named by fourteen of the fourteen models and Insightful by eight and EvaluAgent carries 41 labels and Insightful 14, so the shares are not directly comparable.

EvaluAgent

accepted challenger

Named in one category this edition.

Insightful

accepted challenger

Named in one category this edition.

First-choice share17%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#7A position in a field of 17; printed, not drawn.
Labels4114A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, EvaluAgent reading right to left. Rank and label count are printed, not drawn.Zendesk QA was named alongside these two in eight of the fourteen direct answers. Voxjar vs EvaluAgent · Voxjar vs Insightful · EvaluAgent vs MaestroQA

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; every quote names the model and the prompt it came from. Both figures come from the contact center quality assurance page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
EvaluAgentFirst choices, of fourteen modelsInsightful
Direct21
Paraphrase40
Comparative00
Budget-constrained21
Scale-constrained00
Negative00
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where EvaluAgent and Insightful stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
EvaluAgent Insightful first choice named as an alternative argued againstblank: not namedEach cell is one answer, EvaluAgent on the left and Insightful on the right.

The direct prompt

The plain question, one answer per model, grouped by where EvaluAgent and Insightful stood in it.

EvaluAgent first, Insightful not the choice

2 of 14 modelsInsightful was named in the answer but not as the choice, or not at all.
Kimi K2EvaluAgent alternatives: MaestroQA, Observe.AI, Zendesk QA
GPT-6 LunaEvaluAgent alternatives: Level AI, ScorebuddyCX, Zendesk QA

Insightful first, EvaluAgent an alternative

1 of 14 modelsEvaluAgent was named in the answer but not as the choice, or not at all.
Mistral SmallInsightful, Zendesk QA alternatives: CallFinder, EvaluAgent

Neither was the first choice, one was named

8 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5ScorebuddyCX alternatives: CloudTalk, EvaluAgent, Voxjar
GPT-5.4 miniTalkdesk Quality Management alternatives: EvaluAgent, MaestroQA, Salesforce Service Cloud, ScorebuddyCX, my.SQM Auto QA
Gemini 3.5 FlashMaestroQA alternatives: EvaluAgent, Level AI, Scorebuddy, Zendesk QA
Grok 4.20ScorebuddyCX alternatives: CloudTalk, EvaluAgent, Insightful, SQM CX Quality™, Zendesk QA
DeepSeek V4 FlashZendesk QA alternatives: EvaluAgent, Observe.AI, ScorebuddyCX, Voxjar
Qwen 3.7 FlashVoxjar alternatives: EvaluAgent, Insightful, Zendesk QA
GLM 4.7 FlashXPlayvox QM, ScorebuddyCX alternatives: CloudTalk, EvaluAgent
Muse Glimmer 30BPlayvox QM, Scorebuddy alternatives: Balto, CloudTalk, EvaluAgent

Neither was named

3 of 14 modelsThe answer made no first choice from these two in this category.
Perplexity SonarScorebuddy alternatives: Level AI, Rippit, formerly MaestroQA, Talkdesk Quality Management, Voxjar, Zendesk QA
Llama 4 Maverickno first choice
MiniMax M2.5MaestroQA alternatives: Convin, Scorebuddy

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
EvaluAgent leads by six points.
EvaluAgent11%#4 of 13
Insightful6%#6 of 13
The full small business standing →
Mid-marketThe figures above
EvaluAgent leads by twelve points.
EvaluAgent17%#2 of 17
Insightful4%#7 of 17
The full mid-market standing →
Enterprise
EvaluAgent leads by ten points.
EvaluAgent10%#2 of 15
Insightful0%#– of 15
The full enterprise standing →

What the models said about EvaluAgent

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“For most mid-sized B2B companies, EvaluAgent is the best balance of automation, pricing transparency, and ease of use.” Mistral Small · paraphrase prompt · first choice
“My default pick: evaluagent for a mid-market B2B company that wants a dedicated QA tool” GPT-6 Luna · direct prompt · first choice
“The key differentiator for mid-sized B2B teams is usually EvaluAgent” DeepSeek V4 Flash · paraphrase prompt · first choice

What the models said about Insightful

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“Insightful and Zendesk QA are top contenders due to their comprehensive features, ease of use, and strong integration capabilities” Mistral Small · direct prompt · first choice
“Recommendation: Start with Insightful if you have fewer than 20 agents.” Qwen 3.7 Flash · budget prompt · first choice
“Real-time dashboards, smart scorecards, and performance tracking. Highly rated (4.8/5) for mid-size businesses” Grok 4.20 · direct prompt · alternative
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.