HR AI Index

Index › Vendors › ESCO · September 2026 Edition

1 category · Named, not ranked

ESCO

12Judge labels

0First choices

2Negative labels

8 of 12Models named it

1Category

September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.1, every buyer segment counted.

Standing

5 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. ESCO was named 5 times in Skills intelligence, where TalentGuard led with 19%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business60 of 153

under the label threshold

Mid-market26 of 162

under the label threshold

Enterprise35 of 79

under the label threshold

In skills intelligence · 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 ESCO 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.

Category	Function	Share	Rank	Negative rate	Labels	Quadrant
Skills intelligence	Performance and talent management	0%	26 of 162	0%	5	under 10 labels · led by TalentGuard at 19%

Movement

This is the first edition on this tier, so no move can be computed for ESCO 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 ESCO across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Alternative	Mention	Labels
Claude Haiku 4.5	0	1	1
GPT-5.4 mini	1	0	1
Gemini 3.5 Flash	1	0	1
Perplexity Sonar	0	0	0
Grok 4.1 Fast	1	0	1
Mistral Small	0	0	0
DeepSeek V4 Flash	0	1	1
Llama 4 Maverick	0	0	0
Qwen 3.7 Flash	0	0	0
Kimi K2	0	0	0
GLM 4.7 FlashX	0	0	0
MiniMax M2.5	0	0	0

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

Paraphrase12 labelsNone

Comparative0 labelsNone

Budget-constrained0 labelsNone

Scale-constrained0 labelsNone

Negative0 labelsNone

First choiceAlternativeMentionNegative12 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.

“Multilingual, ~14k skills, occupation-linked | Europe-centric ... Global ops in EU” Grok 4.1 Fast · Skills intelligence · paraphrase prompt · alternative

“The Free/Open-Source Alternative: ESCO or O\*NET” Gemini 3.5 Flash · Skills intelligence · paraphrase prompt · alternative

“ESCO is a solid baseline taxonomy and API” GPT-5.4 mini · Skills intelligence · paraphrase 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 ESCO, over the 12 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and ESCO was named but was not.

ProductSame answerTook the first choice insteadHead to head

Lightcast Open Skills10 of 126Not in the top three

O*NET9 of 122Not in the top three

Eightfold AI7 of 122Not in the top three

TechWolf5 of 122Not in the top three

Workday Skills Cloud5 of 120Not in the top three

Gloat4 of 120Not in the top three

iMocha2 of 121Not in the top three

Acorn PLMS2 of 120Not in the top three

Fuel502 of 120Not in the top three

365Talents1 of 121Not 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 ESCO. 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 6 of the 12 answers that named ESCO and are not a share of its labels.

Domains cited

acorn.works5

hrtechsaas.com5

esco.ec.europa.eu4

f6s.com4

jobspipe.dev4

lightcast.io4

peoplemanagingpeople.com4

docs.lightcast.io3

ovi-me.com3

skywork.ai3

Thirty-nine of the thirty-nine domain citations in answers naming ESCO came from somebody else's page.

Pages cited

acorn.works/best/the-8-best-skills-taxonomy-software-in-20265

hrtechsaas.com/blog/skills-intelligence-software5

f6s.com/software/category/skills-taxonomy4

peoplemanagingpeople.com/tools/best-skills-management-software-for-enterprises4

jobspipe.dev/blog/skills-taxonomy3

lightcast.io/open-skills3

ovi-me.com/blog/ai-skills-inference-taxonomy-platforms-20263

aihr.com/blog/skills-ontology2

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 ESCO'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 ESCO, 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 escourtly.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.