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HR AI Index
Index › Products › Valence · October 2026 Edition
1 category · Ranked

Valence

16Judge labels
0First choices
3Negative labels
9 / 14Models named it
1Category
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.7, every buyer segment counted.
Best standing
0% in Coaching platforms for enterprise buyers
Rank 94 of 128 in the mid-market standing
0 of 14 models made it the first choice on the direct prompt; 33% of its 3 labels there were negative.
By buyer segmentRead the same way at every buyer size.
In coaching platforms · 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 Valence 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 rateLabelsQuadrantSince September 2026
Coaching platformsLearning and development0%94 of 12833%3under 10 labels · led by Growthspace at 20%=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.

Movement

Since September 2026, Valence held within the floor in its one category: no change cleared 13 points.

Best category · Coaching platforms · by segment

Small businessgoneNot named this edition; 2% in September 2026.
0%from 2% in September 2026
Inside the floor by 11 pointsNot ranked
Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 23 → 87 of 117
Enterprise=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 11 → 13 of 50

All categories · Mid-market

CategorySeptember 2026NowChangeReadingRank
Coaching platforms0%0%=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Within noiseRank 23 → 94 of 128

Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.

The floor is 13 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions

By model

How each model treated Valence across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
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ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini01001
Gemini 3.5 Flash00000
Perplexity Sonar00000
Grok 4.1 Fast00000
Mistral Small00000
DeepSeek V4 Flash01001
Llama 4 Maverick00000
Qwen 3.7 Flash00000
Kimi K200011
GLM 4.7 FlashX00000
MiniMax M2.500000
GPT-6 Luna00000
Muse Glimmer 30B00000

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
Direct2 labelsNone
Paraphrase1 labelNone
Comparative8 labelsNone
Budget-constrained1 labelNone
Scale-constrained1 labelNone
Negative3 labelsNone
First choiceAlternativeMentionNegative16 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.

“Valence or Coachello — If you want AI-first scalability for broader deployment at lower cost.” DeepSeek V4 Flash · Coaching platforms · scale prompt · alternative
“Valence or CoachHub are often better if you want coaching to be more broadly accessible” GPT-5.4 mini · Coaching platforms · direct prompt · alternative

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.

“What to Avoid ... No human coaches; mid-sized companies usually want human touch” Kimi K2 · Coaching platforms · paraphrase prompt · hard negative

Named alongside

The products named in the same answers as Valence, over the 16 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Valence was named but was not.
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ProductSame answerTook the first choice insteadHead to head
CoachHub15 of 162Not among the top eight
BetterUp14 of 167Not among the top eight
EZRA13 of 161Not among the top eight
Torch13 of 160Not among the top eight
Exec8 of 160Not among the top eight
Risely7 of 161Not among the top eight
Boon Health6 of 160Not among the top eight
Coachello6 of 160Not among the top eight
Sounding Board6 of 160Not among the top eight
Growthspace5 of 160Not among the top eight
A head-to-head page exists where both products are among a category's top eight. 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 Valence. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 15 of the 16 answers that named Valence and are not a share of its labels.

Domains cited

boon-health.com10
exec.com10
coachello.ai9
torch.io9
risely.me8
easygenerator.com7
simply.coach7
thinkific.com7
entrepreneurshq.com4
zendikt.com4

No domain is on file for Valence, so its own site is not marked.

Pages cited

Pages are listed as the models cited them.

Search and answers

Where Valence stands in Google search beside where it stands in the models' answers.
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In search

Google, US estimates
Searches for its name, Google
33,100 a month (“valence”)
AI search demand for its name, est.
13,398 a month
Its own site
No site of its own on file, so no site figures

In answers

This edition
Share of first choices
0%
rank 94 of 128 in coaching platforms
Segment leader
20%
Growthspace
First choices
0 across its categories
Named in
16 answers
Its own site cited
No site on file to match

Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.

Names read as Valence

What the judge wrote, as written, with how often. The vendor table decides that these count as Valence; a claim can dispute any of them.
Valence/Nadia AI-only 1

Follow Valence

An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.

Already following? Everything you follow, with a stop for each.

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 Valence'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 Valence, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

What a new claim receivesHide what a new claim receives

A new claim receives the current edition's vendor brief for Valence by email, built from the raw record of the edition. It shows:

  • where Valence is named, by buyer and by framing, and which cells hold its first choices;
  • the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
  • its vocabulary against the segment leader's, and the pages the models cited;
  • who was chosen in the answers that did not name Valence, and every reason the record gives;
  • a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
  • one page of published figures cleared to show a buyer.
The subscriber app

A verification link goes to your work email; an address at the vendor's own domain is approved on the spot, any other is reviewed by hand. Your email is never published. Claiming gives no say over labels, shares, verdicts or which quotes appear.