Index › Products › Zingg · October 2026 Edition

2 categories · Named, not ranked

Zingg

2Judge labels

0First choices

0Negative labels

2 / 14Models named it

2Categories

October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, every buyer segment counted.

Standing

2 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. Zingg was named 2 times in CIAM and 1 other category, where Frontegg led with 21%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small businessnot named

No model named it for this buyer.

Mid-market36 of 70

under the label threshold

Enterprisenot named

No model named it for this buyer.

In ciam · 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 Zingg 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	Since September 2026
Customer identity and access management	Identity and access	0%	36 of 70	0%	1	under 10 labels · led by Frontegg at 21%
Master data management	Data platform	0%	41 of 92	0%	1	under 10 labels · led by Profisee MDM at 41%

Movement

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

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Model	Alternative	Labels
Claude Haiku 4.5	0	0
GPT-5.4 mini	0	0
Gemini 3.5 Flash	1	1
Perplexity Sonar	0	0
Grok 4.1 Fast	0	0
Mistral Small	0	0
DeepSeek V4 Flash	0	0
Llama 4 Maverick	0	0
Qwen 3.7 Flash	0	0
Kimi K2	0	0
GLM 4.7 FlashX	0	0
MiniMax M2.5	0	0
GPT-6 Luna	0	0
Muse Glimmer 30B	1	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

Direct0 labelsNone

Paraphrase0 labelsNone

Comparative0 labelsNone

Budget-constrained1 labelNone

Scale-constrained1 labelNone

Negative0 labelsNone

First choiceAlternativeMentionNegative2 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.

“Senzing or Zingg (The Developer-First Approach): If you have a highly technical data team... these are excellent, highly precise API-driven entity resolution engines.” Gemini 3.5 Flash · Master data · scale prompt · alternative

“Zingg or Splink open-source matching in your existing warehouse, often < $500/mo infrastructure.” Muse Glimmer 30B · CIAM · budget 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 Zingg, over the 2 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Zingg was named but was not.

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ProductSame answerTook the first choice insteadHead to head

Microsoft Entra External ID1 of 21Not among the top eight

Profisee MDM1 of 21Not among the top eight

Amazon Cognito1 of 20Not among the top eight

Ataccama ONE1 of 20Not among the top eight

Auth01 of 20Not among the top eight

Census1 of 20Not among the top eight

CluedIn1 of 20Not among the top eight

Frontegg1 of 20Not among the top eight

FusionAuth1 of 20Not among the top eight

Hightouch1 of 20Not 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 Zingg. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 1 of the 2 answers that named Zingg and are not a share of its labels.

Domains cited

cybersecuritynews.com1

dmarcreport.com1

expertinsights.com1

g2.com1

getapp.com1

guideflow.com1

guptadeepak.com1

itechguides.com1

misspepper.ai1

pipeline.zoominfo.com1

No domain is on file for Zingg, so its own site is not marked.

Pages cited

cybersecuritynews.com/best-ciam-solutions/amp1

dmarcreport.com/blog/top-10-identity-verification-platforms1

expertinsights.com/identity-and-access-management/top-customer-identity-and-access-managem1

g2.com/categories/identity-and-access-management-iam/free1

getapp.com/all-software/identity-verification/org/small-business1

guideflow.com/blog/ciam-software1

guptadeepak.com/tools/top-10-ciam-solutions1

itechguides.com/best/identity-resolution-software1

Pages are listed as the models cited them.

Search and answers

Where Zingg stands in Google search beside where it stands in the models' answers.

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In search

Google, US estimates

Searches for its name, Google: 210 a month (“zingg”)
AI search demand for its name, est.: 61 a month
Its own site: No site of its own on file, so no site figures

In answers

This edition

Share of first choices

rank 36 of 70 in CIAM

Segment leader

21%

Frontegg

First choices: 0 across its categories
Named in: 2 answers
Its own site cited: No site on file to match

Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.

Follow Zingg

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

What a new claim receivesHide what a new claim receives

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

where Zingg 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 Zingg, 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.