GTM AI Index
Index Vendors › ExecVision · September 2026 Edition
2 categories · Named, not ranked

ExecVision

6Judge labels
0First choices
2Negative labels
4 of 12Models named it
2Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.
Standing
4 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. ExecVision was named 4 times in Conversation intel and 1 other category, where Avoma led with 52%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In conversation intel · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named ExecVision for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
CategoryFunctionShareRankNegative rateLabelsQuadrant
Conversational intelligence and call recordingSales0%77 of 9350%2under 10 labels · led by Avoma at 52%
Sales coaching and trainingSales0%89 of 12450%2under 10 labels · led by SalesHood at 27%

Movement

This is the first edition on this tier, so no move can be computed for ExecVision yet. The next is due October 1, 2026. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated ExecVision across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash00000
Perplexity Sonar00000
Grok 4.1 Fast00112
Mistral Small00101
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash00011
Kimi K200000
GLM 4.7 FlashX00000
MiniMax M2.500000

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct0 labelsNone
Paraphrase0 labelsNone
Comparative2 labelsNone
Budget-constrained0 labelsNone
Scale-constrained2 labelsNone
Negative2 labelsNone
First choiceAlternativeMentionNegative6 labels in all, every segment counted; 0 of the 0 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

No positive label carried a quote.

And against it

Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.

“ExecVision/Wingman (now Clari Copilot): Poor transcription/integration per Reddit; avoid if accuracy critical.” Grok 4.1 Fast · Conversation intel · negative prompt · hard negative
“recurring reports of application errors, slow loading times during peak usage, and connectivity issues” Qwen 3.7 Flash · Sales coaching · negative prompt · soft negative

Named alongside

The products named in the same answers as ExecVision, over the 6 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and ExecVision was named but was not.
ProductSame answerTook the first choice insteadHead to head
Gong6 of 63Not in the top three
Chorus by ZoomInfo5 of 60Not in the top three
MindTickle4 of 60Not in the top three
Fathom3 of 61Not in the top three
Avoma3 of 60Not in the top three
Clari Copilot3 of 60Not in the top three
Salesloft3 of 60Not in the top three
Jiminny2 of 60Not in the top three
LevelEleven2 of 60Not in the top three
Otter.ai2 of 60Not in the top three
A head-to-head page exists where both products are in a category's top three. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named ExecVision. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 1 of the 6 answers that named ExecVision and are not a share of its labels.

Domains cited

alpharun.com1
autobound.ai1
cirrusinsight.com1
cloudtalk.io1
continu.com1
docebo.com1
firstsales.io1
hyperbound.ai1
learn.g2.com1
mailshake.com1

Ten of the ten domain citations in answers naming ExecVision came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Is this your product?

Claim this page

Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when ExecVision's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as ExecVision, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at execvision.com is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.

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