HR AI Index
Index Vendors › HiredScore · September 2026 Edition
3 categories · Named, not ranked

HiredScore

19Judge labels
0First choices
2Negative labels
10 of 12Models named it
3Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.1, every buyer segment counted.
Standing
8 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. HiredScore was named 8 times in AI recruiting assistants and 2 other categories, where GoPerfect led with 19%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In ai recruiting assistants · 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 HiredScore 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
AI recruiting assistantsTalent acquisition0%26 of 840%4under 10 labels · led by GoPerfect at 19%
Talent intelligencePerformance and talent management0%63 of 7733%3under 10 labels · led by Pin at 17%
Internal talent marketplacePerformance and talent management0%83 of 1290%1under 10 labels · led by Fuel50 at 26%

Movement

This is the first edition on this tier, so no move can be computed for HiredScore 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 HiredScore across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500101
GPT-5.4 mini01102
Gemini 3.5 Flash00000
Perplexity Sonar00000
Grok 4.1 Fast00011
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash00101
Kimi K200101
GLM 4.7 FlashX01102
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
Paraphrase3 labelsNone
Comparative13 labelsNone
Budget-constrained0 labelsNone
Scale-constrained1 labelNone
Negative2 labelsNone
First choiceAlternativeMentionNegative19 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.

“if you want a more enterprise-style automation layer for screening, prioritization, and sourcing” GPT-5.4 mini · AI recruiting assistants · paraphrase prompt · alternative
“Focusing on skills-based hiring or internal mobility? → Eightfold or HiredScore” GLM 4.7 FlashX · AI recruiting assistants · comparative 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.

“Lowest scores (~3.0-3.5) for some like Reejig, HiredScore” Grok 4.1 Fast · Talent intelligence · negative prompt · soft negative

Named alongside

The products named in the same answers as HiredScore, over the 19 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and HiredScore was named but was not.
ProductSame answerTook the first choice insteadHead to head
Eightfold AI17 of 193Not in the top three
Beamery10 of 190Not in the top three
SeekOut9 of 190Not in the top three
hireEZ9 of 190Not in the top three
HireVue8 of 191Not in the top three
Gloat7 of 191Not in the top three
Paradox7 of 190Not in the top three
Phenom7 of 190Not in the top three
Metaview6 of 191Not in the top three
Findem6 of 190Not 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 HiredScore. 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 15 of the 19 answers that named HiredScore and are not a share of its labels.

Domains cited

greenhouse.com8
metaview.ai7
pin.com7
guideflow.com6
hiretruffle.com6
learn.g2.com6
hrtechsaas.com5
g2.com4
jobspipe.dev4
peoplemanagingpeople.com4

Fifty-seven of the fifty-seven domain citations in answers naming HiredScore came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Names read as HiredScore

What the judge wrote, as written, with how often. The vendor table decides that these count as HiredScore; a claim can dispute any of them.
HiredScore AI for Recruiting 1
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 HiredScore'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 HiredScore, 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 hiredscore.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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