HR AI Index

Index › Vendors › MentorCity · September 2026 Edition

1 category · Named, not ranked

MentorCity

14Judge labels

0First choices

1Negative labels

10 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. MentorCity was named 5 times in Mentoring software, where Together led with 37%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business17 of 54

under the label threshold

Mid-market17 of 55

under the label threshold

Enterprise14 of 34

under the label threshold

In mentoring software · 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 MentorCity 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
Mentoring software	Learning and development	0%	17 of 55	0%	5	under 10 labels · led by Together at 37%

Movement

This is the first edition on this tier, so no move can be computed for MentorCity 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 MentorCity 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	0	0
GPT-5.4 mini	0	1	1
Gemini 3.5 Flash	0	0	0
Perplexity Sonar	0	1	1
Grok 4.1 Fast	0	0	0
Mistral Small	0	0	0
DeepSeek V4 Flash	1	0	1
Llama 4 Maverick	0	0	0
Qwen 3.7 Flash	0	1	1
Kimi K2	0	1	1
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

Paraphrase2 labelsNone

Comparative6 labelsNone

Budget-constrained1 labelNone

Scale-constrained2 labelsNone

Negative3 labelsNone

First choiceAlternativeMentionNegative14 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.

“Simple/affordable: MentorCity” DeepSeek V4 Flash · Mentoring software · 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 MentorCity, over the 14 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and MentorCity was named but was not.

ProductSame answerTook the first choice insteadHead to head

Qooper14 of 142Not in the top three

Together13 of 142Not in the top three

MentorcliQ13 of 141Not in the top three

Chronus12 of 142Not in the top three

Mentorloop11 of 141Not in the top three

Ten Thousand Coffees9 of 141Not in the top three

PushFar8 of 141Not in the top three

Guider8 of 140Not in the top three

MentorCloud6 of 140Not in the top three

ADPList5 of 140Not 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 MentorCity. 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 13 of the 14 answers that named MentorCity and are not a share of its labels.

Domains cited

qooper.io12

gartner.com9

brancher.com.au8

chronus.com8

mentorcity.comYour site7

mentorgain.com7

togetherplatform.com6

mentorcliq.com5

guideflow.com4

g2.com3

Sixty-two of the sixty-nine domain citations in answers naming MentorCity came from somebody else's page.

Pages cited

gartner.com/reviews/market/mentoring-software9

chronus.com/blog/top-mentoring-platforms8

brancher.com.au/blog/best-mentoring-software7

mentorcity.com/best-enterprise-mentoring-software6

qooper.io/blog/mentoring-platforms-for-large-companies-and-global-organizations6

mentorgain.com/blog/best-mentorship-software-for-companies4

qooper.io/blog/top-10-online-mentoring-platforms4

growthmentor.com/blog/online-mentoring-platforms-software3

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 MentorCity'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 MentorCity, 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 mentorcity.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.