HR AI Index
Index Vendors › WotNot · September 2026 Edition
1 category · Named, not ranked

WotNot

6Judge labels
2First choices
0Negative labels
6 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
3 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. WotNot was named 3 times in HR AI assistants, where Workativ Assistant led with 12%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In hr ai 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 WotNot 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
HR AI assistantsOnboarding and employee experience2%13 of 1190%3under 10 labels · led by Workativ Assistant at 12%

Movement

This is the first edition on this tier, so no move can be computed for WotNot 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 WotNot across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash00000
Perplexity Sonar00000
Grok 4.1 Fast00000
Mistral Small01001
DeepSeek V4 Flash00000
Llama 4 Maverick10001
Qwen 3.7 Flash01001
Kimi K200000
GLM 4.7 FlashX00000
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
Direct1 label1
Paraphrase4 labels1
Comparative0 labelsNone
Budget-constrained0 labelsNone
Scale-constrained1 labelNone
Negative0 labelsNone
First choiceAlternativeMentionNegative6 labels in all, every segment counted; 2 of the 2 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.

“WotNot - Offers an affordable, no-code chatbot for employee FAQs, candidate screening, and onboarding across multiple channels.” Llama 4 Maverick · HR AI assistants · paraphrase prompt · first choice
“Starts at $29/month; flexible builder; good if HRIS integration isn't a must-have yet” Qwen 3.7 Flash · HR AI assistants · paraphrase prompt · alternative
“WotNot is a good budget-friendly alternative if you want to start small.” Mistral Small · HR AI assistants · 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 WotNot, over the 6 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and WotNot was named but was not.
ProductSame answerTook the first choice insteadHead to head
Workativ Assistant6 of 62Not in the top three
Capacity2 of 61Not in the top three
Rippling2 of 60Not in the top three
MeBeBot1 of 61Not in the top three
Ask BambooHR1 of 60Not in the top three
BambooHR1 of 60Not in the top three
ChatBot1 of 60Not in the top three
ChatGPT1 of 60Not in the top three
Claude1 of 60Not in the top three
Eightfold1 of 60Not 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 WotNot. 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 5 of the 6 answers that named WotNot and are not a share of its labels.

Domains cited

workativ.com5
wotnot.ioYour site5
simular.ai4
hrtechsaas.com3
peoplemanagingpeople.com3
chatbot.com2
herothemes.com2
intervue.io2
moveworks.com2
aiagentsquare.com1

Twenty-four of the twenty-nine domain citations in answers naming WotNot 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 WotNot'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 WotNot, 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 wotnot.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.