HR AI Index

Index › Products › Lusha · September 2026 Edition

1 category · Named, not ranked

Lusha

10Judge labels

0First choices

1Negative labels

7 of 12Models named it

1Category

September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.3, every buyer segment counted.

Standing

4 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. Lusha was named 4 times in Recruiting CRM, where Lever led with 20%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business24 of 104

under the label threshold

Mid-market28 of 88

under the label threshold

Enterprise75 of 80

under the label threshold

In recruiting crm · 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 Lusha 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
Recruiting CRM and sourcing	Talent acquisition	0%	28 of 88	0%	4	under 10 labels · led by Lever at 20%

Movement

This is the first edition on this tier, so no move can be computed for Lusha yet. From the next edition this section shows, per buyer segment and per category, whether its share moved by more than the measured noise floor.

By model

How each model treated Lusha across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

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Model	Alternative	Mention	Labels
Claude Haiku 4.5	0	0	0
GPT-5.4 mini	0	0	0
Gemini 3.5 Flash	1	0	1
Perplexity Sonar	0	0	0
Grok 4.1 Fast	0	0	0
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	1	0	1
MiniMax M2.5	1	0	1

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 labelNone

Paraphrase0 labelsNone

Comparative6 labelsNone

Budget-constrained2 labelsNone

Scale-constrained1 labelNone

Negative0 labelsNone

First choiceAlternativeMentionNegative10 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.

“Contact enrichment; verified emails/phones; integrates with many CRMs.” GLM 4.7 FlashX · Recruiting CRM · comparative prompt · alternative

“SignalHire or Lusha extensions to grab their emails” Gemini 3.5 Flash · Recruiting CRM · budget prompt · alternative

“Need quick verified contact data | Lusha (or ZoomInfo)” MiniMax M2.5 · Recruiting CRM · 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.

No model argued against it.

Named alongside

The products named in the same answers as Lusha, over the 10 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Lusha was named but was not.

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ProductSame answerTook the first choice insteadHead to head

Gem9 of 103Not among the top eight

ContactOut8 of 101Not among the top eight

Manatal8 of 101Not among the top eight

Juicebox7 of 100Not among the top eight

SeekOut7 of 100Not among the top eight

Pin6 of 101Not among the top eight

LinkedIn Recruiter6 of 100Not among the top eight

hireEZ5 of 101Not among the top eight

Loxo4 of 102Not among the top eight

Fetcher4 of 100Not among the top eight

A head-to-head page exists where both products are among a category's top eight. 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 Lusha. 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 8 of the 10 answers that named Lusha and are not a share of its labels.

Domains cited

leonar.app8

selectsoftwarereviews.com8

metaview.ai6

juicebox.ai4

pin.com4

boilr.ai3

gem.com3

matchr.io3

sitepoint.com3

sourcrlab.com3

Forty-five of the forty-five domain citations in answers naming Lusha came from somebody else's page.

Pages cited

leonar.app/blog/best-talent-sourcing-platforms8

selectsoftwarereviews.com/buyer-guide/best-candidate-sourcing-tools8

metaview.ai/resources/blog/candidate-sourcing-tools5

boilr.ai/blog/best-ai-candidate-sourcing-tools-20263

gem.com/blog/candidate-sourcing-software3

juicebox.ai/blog/best-sourcing-tools-for-recruiters3

juicebox.ai/blog/candidate-sourcing-tools3

matchr.io/blog/top-40-best-sourcing-tools3

Pages are listed as the models cited them.

Follow Lusha

An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.

Already following? Everything you follow, with a stop for each.

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 Lusha'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 Lusha, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

With a new claim: the vendor brief

A new claim receives the current edition's vendor brief for Lusha by email, built from the raw record of the edition. It shows:

where Lusha is named, by buyer and by framing, and which cells hold its first choices;
the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
its vocabulary against the segment leader's, and the pages the models cited;
who was chosen in the answers that did not name Lusha, and every reason the record gives;
a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
one page of published figures cleared to show a buyer.

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 lusha.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.