HR AI Index
Index Vendors › CompUp · September 2026 Edition
2 categories · Ranked

CompUp

21Judge labels
8First choices
0Negative labels
8 of 12Models named it
2Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.1, every buyer segment counted.
Best standing
2% in Pay equity for mid-market buyers
Rank 14 of 60 in the mid-market standing
0 of 12 models made it the first choice on the direct prompt; 0% of its 4 labels there were negative.
By buyer segmentRead the same way at every buyer size.
In pay equity · 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 CompUp 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
Pay equityCompensation and total rewards2%14 of 600%4under 10 labels · led by Syndio at 17%
Compensation managementCompensation and total rewards2%15 of 1890%8under 10 labels · led by Pave at 18%

Movement

This is the first edition on this tier, so no move can be computed for CompUp yet. 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 CompUp across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.511103
GPT-5.4 mini10001
Gemini 3.5 Flash03003
Perplexity Sonar00000
Grok 4.1 Fast00000
Mistral Small00000
DeepSeek V4 Flash00202
Llama 4 Maverick10001
Qwen 3.7 Flash00000
Kimi K201001
GLM 4.7 FlashX00000
MiniMax M2.500101

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
Paraphrase4 labels4
Comparative5 labelsNone
Budget-constrained7 labels4
Scale-constrained3 labelsNone
Negative0 labelsNone
First choiceAlternativeMentionNegative21 labels in all, every segment counted; 8 of the 8 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.

“CompUp - A full-stack compensation management platform that is particularly well-suited for mid-sized to large organisations” Llama 4 Maverick · Compensation management · paraphrase prompt · first choice
“If budget is the top priority, start with CompUp.” GPT-5.4 mini · Compensation management · budget prompt · first choice
“Best Overall Choice: CompUp” Claude Haiku 4.5 · Pay equity · paraphrase prompt · first choice
“Strong if you want to run extensive budget simulations, build custom salary bands, and require robust pay equity analysis tools.” Gemini 3.5 Flash · Compensation management · scale 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.

No model argued against it.

Named alongside

The products named in the same answers as CompUp, over the 20 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and CompUp was named but was not.
ProductSame answerTook the first choice insteadHead to head
beqom9 of 200Not in the top three
Pave7 of 204Not in the top three
Comprehensive7 of 202Not in the top three
Deel7 of 200Not in the top three
HRSoft7 of 200Not in the top three
Payscale7 of 200Not in the top three
Aeqium6 of 202Not in the top three
Ravio6 of 201Not in the top three
Compport6 of 200Not in the top three
Syndio5 of 202Not 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 CompUp. 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 16 of the 20 answers that named CompUp and are not a share of its labels.

Domains cited

gartner.com12
guideflow.com9
peoplemanagingpeople.com9
comprehensive.io7
captivateiq.com6
compport.com6
compup.ioYour site6
ravio.com6
hibob.com5
hrtechsaas.com5

Sixty-five of the seventy-one domain citations in answers naming CompUp 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 CompUp'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 CompUp, 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 compup.io 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.