GTM AI Index

Index › Products › Meilisearch · October 2026 Edition

1 category · Named, not ranked

Meilisearch

14Judge labels

0First choices

0Negative labels

6 / 14Models named it

1Category

October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10-05.2, 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. Meilisearch was named 5 times in Ecommerce search, where Algolia led with 25%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business19 of 86

under the label threshold

Mid-market22 of 74

under the label threshold

Enterprisenot named

No model named it for this buyer.

In ecommerce search · 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 Meilisearch 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
Ecommerce search and merchandising	Marketing	0%	22 of 74	0%	5	under 10 labels · led by Algolia at 25%

Movement

This is the first edition on this tier, so no move can be computed for Meilisearch 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 Meilisearch 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	Mention	Labels
Claude Haiku 4.5	0	0	0
GPT-5.4 mini	0	0	0
Gemini 3.5 Flash	0	0	0
Perplexity Sonar	2	0	2
Grok 4.1 Fast	0	0	0
Mistral Small	0	0	0
DeepSeek V4 Flash	0	0	0
Llama 4 Maverick	0	0	0
Qwen 3.7 Flash	0	0	0
Kimi K2	2	1	3
GLM 4.7 FlashX	0	0	0
MiniMax M2.5	0	0	0
GPT-6 Luna	0	0	0
Muse Glimmer 30B	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

Comparative1 labelNone

Budget-constrained4 labelsNone

Scale-constrained3 labelsNone

Negative4 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.

“Open-source search like Meilisearch, Typesense, or Elasticsearch can be cheaper on software cost” Perplexity Sonar · Ecommerce search · budget prompt · alternative

“Have developers, want lowest long-term cost | Meilisearch self-hosted” Kimi K2 · Ecommerce search · budget prompt · alternative

“if you have engineering capacity and want to minimize vendor cost” Perplexity Sonar · Ecommerce search · negative prompt · alternative

“Open-source, fast setup | Budget-conscious, technical teams” Kimi K2 · Ecommerce search · negative 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 Meilisearch, over the 14 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Meilisearch was named but was not.

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ProductSame answerTook the first choice insteadHead to head

Algolia12 of 143Not among the top eight

Typesense12 of 141Not among the top eight

Klevu10 of 142Not among the top eight

Bloomreach Discovery7 of 140Not among the top eight

Elasticsearch7 of 140Not among the top eight

Searchanise6 of 142Not among the top eight

Doofinder5 of 143Not among the top eight

Constructor5 of 140Not among the top eight

Nosto5 of 140Not among the top eight

Searchspring4 of 141Not 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 Meilisearch. 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 11 of the 14 answers that named Meilisearch and are not a share of its labels.

Domains cited

aiproductivity.ai8

netguru.com7

clerk.io6

cs-cart.com6

g2.com6

guideflow.com6

ringly.io6

algolia.com5

gitnux.org5

searchanise.io5

Sixty of the sixty domain citations in answers naming Meilisearch came from somebody else's page.

Pages cited

aiproductivity.ai/blog/best-ecommerce-search-tools8

netguru.com/blog/ecommerce-search-solutions-product-discovery7

cs-cart.com/blog/best-ecommerce-search-engines6

guideflow.com/blog/best-ecommerce-search-software6

gitnux.org/best/ecommerce-merchandising-software5

zoovu.com/blog/best-ecommerce-search-engine5

clerk.io/blog/choosing-search-engine-in-20264

ringly.io/blog/searchspring-alternatives4

Pages are listed as the models cited them.

What it publishes

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Addresses on meilisearch.com

845

subdomains included

Content

325

counted in the table below

Documentation

440

Product · Integration

16 · 23

Kind	Pages	Last 90 days	Latest
Blog	279	5	2026-09-23
Comparison	37	4	2026-10-01
Glossary or explainer	6	0	2026-03-10
News or press	2	undated
Template or tool	1	undated

Most recent

2026-10-01Full text search vs semantic search comparison
2026-09-23Raptor rag blog
2026-09-17Diagnose slow saas search blog
2026-09-09Agentic search blog
2026-09-01Opensearch alternatives comparison
2026-08-27Lucene alternatives comparison

How it is countedHide how it is counted

Every page meilisearch.com exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. Read October 5, 2026.

Follow Meilisearch

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.

The company

Meilisearch is its own company.

ShowHide

In its own words

Stated by the vendor, not checked

Positioning: One platform to build, scale, and unify search and AI retrieval
meilisearch.com
For: teams
meilisearch.com
Price stated: $20 meilisearch.com
Starting price: 20 meilisearch.com
Free plan or trial: 14-day free trial, no credit card required meilisearch.com
Integrations claimed: 3 meilisearch.com/products/rag
Certifications: SOC 2 Type IIGDPRSOC 2 Type II certifiedSOC2 type 2 report
Customers named: CarbonGraphHugging FaceLouis VuittonBookshop.orgCarJagerSamtecScenarioTouchless
Not stated on the pages read: Hosting

What Meilisearch's own pages state, read October 5, 2026: meilisearch.com, meilisearch.com/pricing, trust.meilisearch.com, meilisearch.com/products/rag, meilisearch.com/customers. A claimed page can correct any of 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 Meilisearch'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 Meilisearch, 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 Meilisearch by email, built from the raw record of the edition. It shows:

where Meilisearch 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 Meilisearch, 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.