AI Indexes
GTM AI Index
Index › Customer › Contact center QA › EvaluAgent vs CloudTalk
Contact center quality assurance · October 2026 Edition

EvaluAgent vs CloudTalk

Six of fourteen models named EvaluAgent first on the direct prompt; zero named CloudTalk. EvaluAgent was named by fourteen of the fourteen models and CloudTalk by nine and EvaluAgent carries 45 labels and CloudTalk 15, so the shares are not directly comparable.

EvaluAgent

accepted challenger

Named in one category this edition.

CloudTalk

accepted challenger

Named in thirteen categories this edition.

First-choice share28%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate4%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#5A position in a field of 13; printed, not drawn.
Labels4515A 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.Scorebuddy was named alongside these two in ten of the fourteen direct answers. EvaluAgent vs Scorebuddy · EvaluAgent vs Zendesk QA · EvaluAgent vs Playvox QM

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 modelsCloudTalk
Direct60
Paraphrase30
Comparative00
Budget-constrained52
Scale-constrained00
Negative102 against EvaluAgent
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.

Across every category in the October 2026 Edition, EvaluAgent and CloudTalk were named in the same answer forty-two times, of the 109 answers naming EvaluAgent and the 358 naming CloudTalk. In those answers CloudTalk took the first choice eleven times and EvaluAgent eleven.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where EvaluAgent and CloudTalk stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
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 CloudTalk first choice named as an alternative argued againstblank: not namedEach cell is one answer, EvaluAgent on the left and CloudTalk on the right.

The direct prompt

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

EvaluAgent first, CloudTalk not the choice

6 of 14 modelsCloudTalk was named in the answer but not as the choice, or not at all.
Grok 4.1 FastEvaluAgent, Scorebuddy alternatives: Balto, Talkdesk QM, Zendesk QA
Mistral SmallEvaluAgent, Scorebuddy alternatives: Talkdesk
DeepSeek V4 FlashEvaluAgent alternatives: AmplifAI, Observe.AI, Scorebuddy, Talkdesk, Zendesk QA
Llama 4 MaverickEvaluAgent alternatives: GetApp, Scorebuddy
Kimi K2EvaluAgent alternatives: Playvox, ScorebuddyCX, Zendesk QA
GPT-6 LunaEvaluAgent alternatives: CallMiner Eureka, NICE CXone Quality Management

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Scorebuddy alternatives: Convin, EvaluAgent, Gong, Level AI
Gemini 3.5 FlashZendesk QA alternatives: EvaluAgent, Level AI, MaestroQA
Perplexity SonarScorebuddy alternatives: AmplifAI, Balto, EvaluAgent, Level AI
GLM 4.7 FlashXAmplifAI, Balto alternatives: EvaluAgent, Playvox QM, Scorebuddy
MiniMax M2.5Scorebuddy alternatives: EvaluAgent, Voxjar, Zendesk QA
Muse Glimmer 30BObserve.AI, Zendesk QA alternatives: EvaluAgent, Playvox, Scorebuddy

Neither was named

2 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniLevel AI alternatives: Calabrio ONE, Scorebuddy, Zendesk QA
Qwen 3.7 FlashCallMiner Eureka alternatives: Five9 Agent Connect, MaestroQA, NICE CXone Quality Management, Playvox

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 four points.
EvaluAgent19%#1 of 12
CloudTalk15%#2 of 12
The full small business standing →
Mid-marketThe figures above
EvaluAgent leads by twenty-four points.
EvaluAgent28%#1 of 13
CloudTalk4%#5 of 13
The full mid-market standing →
Enterprise
CloudTalk is not named for this buyer.
EvaluAgent9%#5 of 14
CloudTalk—not named
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. Five of six in this category shown.

“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 CloudTalk

No label in this category carried a quote.

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.