Enterprise search platform rank

As of

All 16 companies by recommendation prompt presence

Elastic Search AI leads at 41.7%; the middle of the board sits at 6.3%.

Ahead of second place: 8.3%
Held by the top three: 58%
Middle of the board: 6.3%
Below half the leader: 13 of 16

Rank, name and recommendation prompt presenceMiddle 6.3%

1Elastic Search AI41.7%
2GoSearch33.3%
3Glean29.2%
4Onyx AI20.8%
5Coveo16.7%
6Azure AI Search16.7%
7Sinequa8.3%
8Lucidworks8.3%
9Vertex AI Search4.2%
10IBM watsonx Discovery0.0%
11Algolia0.0%
12Amazon Kendra0.0%
13deepset AI Platform0.0%
14Guru0.0%
15Vectara0.0%
16Yext Search0.0%

The prompt boards are re-run in rotation, about one category a day, so each board refreshes every few weeks and shows the date of its snapshot.

24 checks behind each row · 100% confidence across rows.

Enterprise search platform rank current rankings
Rank	Name	Recommendation prompt presence	Mention coverage	Share of names	Cited as source	Change	Why
01	Elastic Search AI	41.7%	38.89% · 14 / 36	20.29% · 14 / 69	9.68% · 3 / 31	1	This rank My rank
02	GoSearch	33.3%	30.56% · 11 / 36	15.94% · 11 / 69	32.26% · 10 / 31	3	This rank My rank
03	Glean	29.2%	30.56% · 11 / 36	15.94% · 11 / 69	22.58% · 7 / 31	2	This rank My rank
04	Onyx AI	20.8%	16.67% · 6 / 36	8.7% · 6 / 69	16.13% · 5 / 31	2	This rank My rank
05	Coveo	16.7%	25% · 9 / 36	13.04% · 9 / 69	6.45% · 2 / 31	1	This rank My rank
06	Azure AI Search	16.7%	16.67% · 6 / 36	8.7% · 6 / 69	6.45% · 2 / 31	3	This rank My rank
07	Sinequa	8.3%	13.89% · 5 / 36	7.25% · 5 / 69	0% · 0 / 31		This rank My rank
08	Lucidworks	8.3%	11.11% · 4 / 36	5.8% · 4 / 69	0% · 0 / 31		This rank My rank
09	Vertex AI Search	4.2%	2.78% · 1 / 36	1.45% · 1 / 69	3.23% · 1 / 31	6	This rank My rank
10	IBM watsonx Discovery	0.0%	2.78% · 1 / 36	1.45% · 1 / 69	3.23% · 1 / 31	1	This rank My rank
11	Algolia	0.0%	2.78% · 1 / 36	1.45% · 1 / 69	0% · 0 / 31	1	Showing My rank
12	Amazon Kendra	0.0%	0% · 0 / 36	0% · 0 / 69	0% · 0 / 31	2	This rank My rank
13	deepset AI Platform	0.0%	0% · 0 / 36	0% · 0 / 69	0% · 0 / 31		This rank My rank
14	Guru	0.0%	0% · 0 / 36	0% · 0 / 69	0% · 0 / 31	5	This rank My rank
15	Vectara	0.0%	0% · 0 / 36	0% · 0 / 69	0% · 0 / 31	1	This rank My rank
16	Yext Search	0.0%	0% · 0 / 36	0% · 0 / 69	0% · 0 / 31		This rank My rank

24 checks behind each row · 100% confidence across rows.

Enterprise search platform rank current rankings
Rank	Name	Recommendation prompt presence	Mention coverage	Share of names	Cited as source	Change	Why
01	Elastic Search AI	41.7%	38.89% · 14 / 36	20.29% · 14 / 69	9.68% · 3 / 31	1	This rank My rank
02	GoSearch	33.3%	30.56% · 11 / 36	15.94% · 11 / 69	32.26% · 10 / 31	3	This rank My rank
03	Glean	29.2%	30.56% · 11 / 36	15.94% · 11 / 69	22.58% · 7 / 31	2	This rank My rank
04	Onyx AI	20.8%	16.67% · 6 / 36	8.7% · 6 / 69	16.13% · 5 / 31	2	This rank My rank
05	Coveo	16.7%	25% · 9 / 36	13.04% · 9 / 69	6.45% · 2 / 31	1	This rank My rank
06	Azure AI Search	16.7%	16.67% · 6 / 36	8.7% · 6 / 69	6.45% · 2 / 31	3	This rank My rank
07	Sinequa	8.3%	13.89% · 5 / 36	7.25% · 5 / 69	0% · 0 / 31		This rank My rank
08	Lucidworks	8.3%	11.11% · 4 / 36	5.8% · 4 / 69	0% · 0 / 31		This rank My rank
09	Vertex AI Search	4.2%	2.78% · 1 / 36	1.45% · 1 / 69	3.23% · 1 / 31	6	This rank My rank
10	IBM watsonx Discovery	0.0%	2.78% · 1 / 36	1.45% · 1 / 69	3.23% · 1 / 31	1	This rank My rank
11	Algolia	0.0%	2.78% · 1 / 36	1.45% · 1 / 69	0% · 0 / 31	1	Showing My rank
12	Amazon Kendra	0.0%	0% · 0 / 36	0% · 0 / 69	0% · 0 / 31	2	This rank My rank
13	deepset AI Platform	0.0%	0% · 0 / 36	0% · 0 / 69	0% · 0 / 31		This rank My rank
14	Guru	0.0%	0% · 0 / 36	0% · 0 / 69	0% · 0 / 31	5	This rank My rank
15	Vectara	0.0%	0% · 0 / 36	0% · 0 / 69	0% · 0 / 31	1	This rank My rank
16	Yext Search	0.0%	0% · 0 / 36	0% · 0 / 69	0% · 0 / 31		This rank My rank

Primary brandQuestion typeModel APIQuestion contains

Run a question live

30.6%

of these answers name or cite Glean

11 of 36 answers

31.4%

Its share of the compared brands' appearances

7

Answers citing its own site

7 links to its domains

2 of 3

Model APIs that name it

The compared brands across the filtered answers
Brand	Named or cited	Against primary	Share of compared	Mentions	Answers citing it	Links to its site	Model APIs
Elastic Search AIelastic.co	38.9%14 of 36	+8.3 pts	40.0%	26	3	3	3 of 3
Gleanglean.com	30.6%11 of 36	Primary	31.4%	23	7	7	2 of 3
Coveocoveo.com	25.0%9 of 36	-5.6 pts	25.7%	20	1	2	2 of 3
Algoliaalgolia.com	2.8%1 of 36	-27.8 pts	2.9%	1	0	0	1 of 3

Compared brands named in each answer, by question and model API
Question	OpenAIopenai/gpt-4o-mini	Anthropicanthropic/claude-haiku-4-5	Geminigoogle/gemini-2.5-flash
01What are the best AI-powered enterprise search platforms for securely finding internal company knowledge?Recommendation	Glean, cited 1CoveoElastic Search AI 6 sources`7f88db22`	None named 0 sources`225b80c4`	GleanCoveoElastic Search AI 9 sources`7fdc28a9`
02Recommend a workplace search platform that connects collaboration, document, ticketing, and CRM systems while preserving permissions.Recommendation	Glean, cited 1Elastic Search AI 5 sources`7c641b34`	None named 0 sources`b24e079f`	Glean, cited 1 3 sources`cd78a150`
03Which enterprise knowledge-search platform is best for a regulated organization needing document-level access controls and audit trails?Recommendation	None named 5 sources`89239e04`	None named 0 sources`c0c08f73`	None named 9 sources`f2c83250`
04Recommend an open-source or self-hosted enterprise search platform for private retrieval-augmented generation.Recommendation	Elastic Search AI 6 sources`4032f71e`	Elastic Search AI 0 sources`b4dda326`	None named 6 sources`8d357e16`
05Which developer platform is best for hybrid keyword and vector retrieval, semantic reranking, and high-scale search?Recommendation	Elastic Search AI, cited 1 7 sources`7d0b6765`	None named 0 sources`fc2fc78d`	Elastic Search AI, cited 1 9 sources`da9acbef`
06Recommend a managed retrieval service for building grounded enterprise assistants with citations and source provenance.Recommendation	None named 5 sources`c5b85d74`	None named 0 sources`d3607312`	None named 7 sources`9e722e80`
07Which enterprise search tools offer broad application connectors, fast content refresh, and permission-aware results?Recommendation	Glean, cited 1CoveoElastic Search AI 8 sources`7d0d0721`	None named 0 sources`876516ad`	Glean 7 sources`aa756d83`
08What enterprise search platform should a global company evaluate for multilingual content, regional deployment, and access control?Recommendation	Glean, cited 1CoveoElastic Search AI 5 sources`c34f2426`	None named 0 sources`ff7c556c`	Elastic Search AI, cited 1 8 sources`29b57bea`
09Compare enterprise AI search platforms on connectors, relevance, permissions, governance, deployment options, and analytics.Commercial comparison	Glean, cited 1Coveo, cited 2 7 sources`22ed413d`	None named 0 sources`f583827f`	Glean, cited 1CoveoElastic Search AIAlgolia 7 sources`3f99bec0`
10How should buyers compare retrieval platforms for grounded AI on accuracy, latency, observability, and total cost?Commercial comparison	None named 0 sources`8d80c11d`	None named 0 sources`cdd75513`	None named 6 sources`61bd76c8`
11Which enterprise search vendors support private-cloud or on-premises deployment, model flexibility, and customer-managed encryption?Commercial comparison	GleanCoveoElastic Search AI 2 sources`3bda5ade`	None named 0 sources`d5030b4e`	None named 9 sources`29bb6686`
12Create a vendor shortlist and proof-of-concept scorecard for modernizing enterprise search and knowledge retrieval.Commercial comparison	GleanCoveoElastic Search AI 0 sources`a7ecb668`	None named 0 sources`430bbce5`	CoveoElastic Search AI 0 sources`3e11ecf7`

Sites cited in the filtered answers
Site	Answers citing it	Distinct pages	Model APIs	Best position
gosearch.ai	10	6	2	1
glean.com	7	5	2	1
moveworks.com	6	6	2	3
onyx.app	5	2	2	1
rank.ai	4	4	2	1
chapsvision.com	4	1	2	2
bloomfire.com	3	3	2	1
elastic.co	3	3	2	3
kore.ai	3	2	2	1
instaclustr.com	3	1	1	1
slack.com	3	1	2	4
gartner.com	2	2	2	2
medium.com	2	2	1	2
meilisearch.com	2	2	1	4
youtube.com	2	2	2	6
github.com	2	1	2	1
squirro.com	2	1	2	1
superlinked.com	2	1	2	1
techcommunity.microsoft.com	2	1	2	1
firecrawl.dev	2	1	2	2

What this report publishesThe public buying questions, the brands each answer names, the sources it cites and a fingerprint of each answer. Answer text is not published, and no customer data is in it.enterprise-search-platforms-2026-07-27 / 4-enterprise-search-platforms-2026-07-27-models-64232fd32583

Primary brandQuestion typeModel APIQuestion contains

Run a question live

30.6%

of these answers name or cite Glean

11 of 36 answers

31.4%

Its share of the compared brands' appearances

7

Answers citing its own site

7 links to its domains

2 of 3

Model APIs that name it

The compared brands across the filtered answers
Brand	Named or cited	Against primary	Share of compared	Mentions	Answers citing it	Links to its site	Model APIs
Elastic Search AIelastic.co	38.9%14 of 36	+8.3 pts	40.0%	26	3	3	3 of 3
Gleanglean.com	30.6%11 of 36	Primary	31.4%	23	7	7	2 of 3
Coveocoveo.com	25.0%9 of 36	-5.6 pts	25.7%	20	1	2	2 of 3
Algoliaalgolia.com	2.8%1 of 36	-27.8 pts	2.9%	1	0	0	1 of 3

Compared brands named in each answer, by question and model API
Question	OpenAIopenai/gpt-4o-mini	Anthropicanthropic/claude-haiku-4-5	Geminigoogle/gemini-2.5-flash
01What are the best AI-powered enterprise search platforms for securely finding internal company knowledge?Recommendation	Glean, cited 1CoveoElastic Search AI 6 sources`7f88db22`	None named 0 sources`225b80c4`	GleanCoveoElastic Search AI 9 sources`7fdc28a9`
02Recommend a workplace search platform that connects collaboration, document, ticketing, and CRM systems while preserving permissions.Recommendation	Glean, cited 1Elastic Search AI 5 sources`7c641b34`	None named 0 sources`b24e079f`	Glean, cited 1 3 sources`cd78a150`
03Which enterprise knowledge-search platform is best for a regulated organization needing document-level access controls and audit trails?Recommendation	None named 5 sources`89239e04`	None named 0 sources`c0c08f73`	None named 9 sources`f2c83250`
04Recommend an open-source or self-hosted enterprise search platform for private retrieval-augmented generation.Recommendation	Elastic Search AI 6 sources`4032f71e`	Elastic Search AI 0 sources`b4dda326`	None named 6 sources`8d357e16`
05Which developer platform is best for hybrid keyword and vector retrieval, semantic reranking, and high-scale search?Recommendation	Elastic Search AI, cited 1 7 sources`7d0b6765`	None named 0 sources`fc2fc78d`	Elastic Search AI, cited 1 9 sources`da9acbef`
06Recommend a managed retrieval service for building grounded enterprise assistants with citations and source provenance.Recommendation	None named 5 sources`c5b85d74`	None named 0 sources`d3607312`	None named 7 sources`9e722e80`
07Which enterprise search tools offer broad application connectors, fast content refresh, and permission-aware results?Recommendation	Glean, cited 1CoveoElastic Search AI 8 sources`7d0d0721`	None named 0 sources`876516ad`	Glean 7 sources`aa756d83`
08What enterprise search platform should a global company evaluate for multilingual content, regional deployment, and access control?Recommendation	Glean, cited 1CoveoElastic Search AI 5 sources`c34f2426`	None named 0 sources`ff7c556c`	Elastic Search AI, cited 1 8 sources`29b57bea`
09Compare enterprise AI search platforms on connectors, relevance, permissions, governance, deployment options, and analytics.Commercial comparison	Glean, cited 1Coveo, cited 2 7 sources`22ed413d`	None named 0 sources`f583827f`	Glean, cited 1CoveoElastic Search AIAlgolia 7 sources`3f99bec0`
10How should buyers compare retrieval platforms for grounded AI on accuracy, latency, observability, and total cost?Commercial comparison	None named 0 sources`8d80c11d`	None named 0 sources`cdd75513`	None named 6 sources`61bd76c8`
11Which enterprise search vendors support private-cloud or on-premises deployment, model flexibility, and customer-managed encryption?Commercial comparison	GleanCoveoElastic Search AI 2 sources`3bda5ade`	None named 0 sources`d5030b4e`	None named 9 sources`29bb6686`
12Create a vendor shortlist and proof-of-concept scorecard for modernizing enterprise search and knowledge retrieval.Commercial comparison	GleanCoveoElastic Search AI 0 sources`a7ecb668`	None named 0 sources`430bbce5`	CoveoElastic Search AI 0 sources`3e11ecf7`

Sites cited in the filtered answers
Site	Answers citing it	Distinct pages	Model APIs	Best position
gosearch.ai	10	6	2	1
glean.com	7	5	2	1
moveworks.com	6	6	2	3
onyx.app	5	2	2	1
rank.ai	4	4	2	1
chapsvision.com	4	1	2	2
bloomfire.com	3	3	2	1
elastic.co	3	3	2	3
kore.ai	3	2	2	1
instaclustr.com	3	1	1	1
slack.com	3	1	2	4
gartner.com	2	2	2	2
medium.com	2	2	1	2
meilisearch.com	2	2	1	4
youtube.com	2	2	2	6
github.com	2	1	2	1
squirro.com	2	1	2	1
superlinked.com	2	1	2	1
techcommunity.microsoft.com	2	1	2	1
firecrawl.dev	2	1	2	2

What this report publishesThe public buying questions, the brands each answer names, the sources it cites and a fingerprint of each answer. Answer text is not published, and no customer data is in it.enterprise-search-platforms-2026-07-27 / 4-enterprise-search-platforms-2026-07-27-models-64232fd32583

Ranks a reviewed Enterprise Search brand universe using a fixed, public set of neutral commercial prompts across 3 AI providers.

11

Rank on this board

0 percent

Score

24

Answers behind the score

100% confidence · 1 of 1 components evidenced

What the score is built from

1 of 1 evidenced

Every component evidenced · 1 evidence record each

Components of Algolia's score
Component	Value	Contribution
Recommendation presence	0	0

Moved up since the previous snapshot

+1 places

Gemini brand mention coverage0 to 8.333
+8.333
OpenAI brand mention coverage8.333 to 0
-8.333
Mention share1.923 to 1.449
-0.474
Anthropic brand mention coverage0 to 0
0
Anthropic brand recommendation presence0 to 0
0
Citation share0 to 0
0
Engine breadth1 to 1
0
Mention coverage2.778 to 2.778
0
Recommendation presence0 to 0
0
Gemini brand citation share0 to 0
0
Gemini brand recommendation presence0 to 0
0
OpenAI brand citation share0 to 0
0
OpenAI brand recommendation presence0 to 0
0

Where each number comes from

13 public records

Anthropic mention coverageAnthropic brand mention coverage · observed Sep 15, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
Anthropic recommendation-prompt presenceAnthropic brand recommendation presence · observed Sep 15, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"enterprise-search-platforms-2026-07-27","runArtifactIds":["6f2c67bc-e104-4095-a6bd-25ae19947d22","bd7f7fee-6dc8-4cfa-9981-39b48f151400","bbc0d259-e343-4fc1-bd38-8c083189d22a","eee356de-14f9-4159-aeb9-1e69e5d6b294","e03c915c-ead1-44c4-96c1-a93363a6ef21","c03c2534-9e4c-48ff-81a9-b2a7e9c8730a","5ae4d15b-56f4-459b-bb8a-81804676ce42","8037f38c-d5ca-41a9-b347-a2e3edce6bb0","2084e267-b130-46dd-a324-d9d4a002fe84","5a046903-9590-40cb-9760-e46697c492f9","92802ab0-d132-432f-aa2d-87b41e00454a","bdafbc22-ebe6-43e7-a7a1-289c366f9b74","8307fc24-0ade-4ddf-ad3a-a6fcea5d93a6","73e2713f-62db-497e-b209-5f5e311398fe","793dc143-c0c4-4fb9-ad49-b4634dd95925","c669b4dc-3397-4ffa-831b-0c731022c116","d0ab3936-ef13-4808-b883-45c1f6d21a44","dd1944e5-d40e-4b56-bc3e-e541266d6490","7ae9ca44-af22-4905-9a4b-6428ea8f6e5e","0829f5c8-2e6c-489b-b136-de6ebaa7ef6b","9c282344-655e-45f8-adc1-7dd09b970210","853c4909-7dc7-4c74-bf90-1938499036c0","403f6610-5ceb-4d11-aef4-a65e279959aa","0cedc829-b078-46d5-b911-5110d2eaf0e8","b2f618bc-c0c2-4e13-9974-96b807b8c91d","ee70b1b1-ea54-4219-9a4b-5ce091234f6f","64e595c9-b413-4a89-b386-1981d7ce6b55","21eca9cc-9c2f-4ad2-adf7-af89b4f39a30","c7289ecc-5746-447b-8492-600a8e5ed5b3","d17c55f0-09c6-4ea9-9b88-e54370dd71c1","ec0cfb82-0877-42d5-91c3-6da2689f65e3","fb20c0a7-3a7f-4d05-87aa-f4b72c852473","d2025f50-d778-41c3-8f0e-40ec00ca03d7","755c247c-561f-4757-8be7-1eb12e9e0013","5f9b36ad-1ac5-4f81-a9ad-6fb57f82b9ae","515a685c-fc8d-47da-982b-81a1a06e6f4b"],"benchmarkVersion":"4-enterprise-search-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Citation shareCitation share · observed Sep 15, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"enterprise-search-platforms-2026-07-27","runArtifactIds":["6f2c67bc-e104-4095-a6bd-25ae19947d22","bd7f7fee-6dc8-4cfa-9981-39b48f151400","bbc0d259-e343-4fc1-bd38-8c083189d22a","eee356de-14f9-4159-aeb9-1e69e5d6b294","e03c915c-ead1-44c4-96c1-a93363a6ef21","c03c2534-9e4c-48ff-81a9-b2a7e9c8730a","5ae4d15b-56f4-459b-bb8a-81804676ce42","8037f38c-d5ca-41a9-b347-a2e3edce6bb0","2084e267-b130-46dd-a324-d9d4a002fe84","5a046903-9590-40cb-9760-e46697c492f9","92802ab0-d132-432f-aa2d-87b41e00454a","bdafbc22-ebe6-43e7-a7a1-289c366f9b74","8307fc24-0ade-4ddf-ad3a-a6fcea5d93a6","73e2713f-62db-497e-b209-5f5e311398fe","793dc143-c0c4-4fb9-ad49-b4634dd95925","c669b4dc-3397-4ffa-831b-0c731022c116","d0ab3936-ef13-4808-b883-45c1f6d21a44","dd1944e5-d40e-4b56-bc3e-e541266d6490","7ae9ca44-af22-4905-9a4b-6428ea8f6e5e","0829f5c8-2e6c-489b-b136-de6ebaa7ef6b","9c282344-655e-45f8-adc1-7dd09b970210","853c4909-7dc7-4c74-bf90-1938499036c0","403f6610-5ceb-4d11-aef4-a65e279959aa","0cedc829-b078-46d5-b911-5110d2eaf0e8","b2f618bc-c0c2-4e13-9974-96b807b8c91d","ee70b1b1-ea54-4219-9a4b-5ce091234f6f","64e595c9-b413-4a89-b386-1981d7ce6b55","21eca9cc-9c2f-4ad2-adf7-af89b4f39a30","c7289ecc-5746-447b-8492-600a8e5ed5b3","d17c55f0-09c6-4ea9-9b88-e54370dd71c1","ec0cfb82-0877-42d5-91c3-6da2689f65e3","fb20c0a7-3a7f-4d05-87aa-f4b72c852473","d2025f50-d778-41c3-8f0e-40ec00ca03d7","755c247c-561f-4757-8be7-1eb12e9e0013","5f9b36ad-1ac5-4f81-a9ad-6fb57f82b9ae","515a685c-fc8d-47da-982b-81a1a06e6f4b"],"benchmarkVersion":"4-enterprise-search-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Engine breadthEngine breadth · observed Sep 15, 2026, 12:00 AM UTC1 engines100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"enterprise-search-platforms-2026-07-27","runArtifactIds":["6f2c67bc-e104-4095-a6bd-25ae19947d22","bd7f7fee-6dc8-4cfa-9981-39b48f151400","bbc0d259-e343-4fc1-bd38-8c083189d22a","eee356de-14f9-4159-aeb9-1e69e5d6b294","e03c915c-ead1-44c4-96c1-a93363a6ef21","c03c2534-9e4c-48ff-81a9-b2a7e9c8730a","5ae4d15b-56f4-459b-bb8a-81804676ce42","8037f38c-d5ca-41a9-b347-a2e3edce6bb0","2084e267-b130-46dd-a324-d9d4a002fe84","5a046903-9590-40cb-9760-e46697c492f9","92802ab0-d132-432f-aa2d-87b41e00454a","bdafbc22-ebe6-43e7-a7a1-289c366f9b74","8307fc24-0ade-4ddf-ad3a-a6fcea5d93a6","73e2713f-62db-497e-b209-5f5e311398fe","793dc143-c0c4-4fb9-ad49-b4634dd95925","c669b4dc-3397-4ffa-831b-0c731022c116","d0ab3936-ef13-4808-b883-45c1f6d21a44","dd1944e5-d40e-4b56-bc3e-e541266d6490","7ae9ca44-af22-4905-9a4b-6428ea8f6e5e","0829f5c8-2e6c-489b-b136-de6ebaa7ef6b","9c282344-655e-45f8-adc1-7dd09b970210","853c4909-7dc7-4c74-bf90-1938499036c0","403f6610-5ceb-4d11-aef4-a65e279959aa","0cedc829-b078-46d5-b911-5110d2eaf0e8","b2f618bc-c0c2-4e13-9974-96b807b8c91d","ee70b1b1-ea54-4219-9a4b-5ce091234f6f","64e595c9-b413-4a89-b386-1981d7ce6b55","21eca9cc-9c2f-4ad2-adf7-af89b4f39a30","c7289ecc-5746-447b-8492-600a8e5ed5b3","d17c55f0-09c6-4ea9-9b88-e54370dd71c1","ec0cfb82-0877-42d5-91c3-6da2689f65e3","fb20c0a7-3a7f-4d05-87aa-f4b72c852473","d2025f50-d778-41c3-8f0e-40ec00ca03d7","755c247c-561f-4757-8be7-1eb12e9e0013","5f9b36ad-1ac5-4f81-a9ad-6fb57f82b9ae","515a685c-fc8d-47da-982b-81a1a06e6f4b"],"benchmarkVersion":"4-enterprise-search-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Mention coverageMention coverage · observed Sep 15, 2026, 12:00 AM UTC2.778 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"enterprise-search-platforms-2026-07-27","runArtifactIds":["6f2c67bc-e104-4095-a6bd-25ae19947d22","bd7f7fee-6dc8-4cfa-9981-39b48f151400","bbc0d259-e343-4fc1-bd38-8c083189d22a","eee356de-14f9-4159-aeb9-1e69e5d6b294","e03c915c-ead1-44c4-96c1-a93363a6ef21","c03c2534-9e4c-48ff-81a9-b2a7e9c8730a","5ae4d15b-56f4-459b-bb8a-81804676ce42","8037f38c-d5ca-41a9-b347-a2e3edce6bb0","2084e267-b130-46dd-a324-d9d4a002fe84","5a046903-9590-40cb-9760-e46697c492f9","92802ab0-d132-432f-aa2d-87b41e00454a","bdafbc22-ebe6-43e7-a7a1-289c366f9b74","8307fc24-0ade-4ddf-ad3a-a6fcea5d93a6","73e2713f-62db-497e-b209-5f5e311398fe","793dc143-c0c4-4fb9-ad49-b4634dd95925","c669b4dc-3397-4ffa-831b-0c731022c116","d0ab3936-ef13-4808-b883-45c1f6d21a44","dd1944e5-d40e-4b56-bc3e-e541266d6490","7ae9ca44-af22-4905-9a4b-6428ea8f6e5e","0829f5c8-2e6c-489b-b136-de6ebaa7ef6b","9c282344-655e-45f8-adc1-7dd09b970210","853c4909-7dc7-4c74-bf90-1938499036c0","403f6610-5ceb-4d11-aef4-a65e279959aa","0cedc829-b078-46d5-b911-5110d2eaf0e8","b2f618bc-c0c2-4e13-9974-96b807b8c91d","ee70b1b1-ea54-4219-9a4b-5ce091234f6f","64e595c9-b413-4a89-b386-1981d7ce6b55","21eca9cc-9c2f-4ad2-adf7-af89b4f39a30","c7289ecc-5746-447b-8492-600a8e5ed5b3","d17c55f0-09c6-4ea9-9b88-e54370dd71c1","ec0cfb82-0877-42d5-91c3-6da2689f65e3","fb20c0a7-3a7f-4d05-87aa-f4b72c852473","d2025f50-d778-41c3-8f0e-40ec00ca03d7","755c247c-561f-4757-8be7-1eb12e9e0013","5f9b36ad-1ac5-4f81-a9ad-6fb57f82b9ae","515a685c-fc8d-47da-982b-81a1a06e6f4b"],"benchmarkVersion":"4-enterprise-search-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Reviewed-brand presence shareMention share · observed Sep 15, 2026, 12:00 AM UTC1.449 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"enterprise-search-platforms-2026-07-27","runArtifactIds":["6f2c67bc-e104-4095-a6bd-25ae19947d22","bd7f7fee-6dc8-4cfa-9981-39b48f151400","bbc0d259-e343-4fc1-bd38-8c083189d22a","eee356de-14f9-4159-aeb9-1e69e5d6b294","e03c915c-ead1-44c4-96c1-a93363a6ef21","c03c2534-9e4c-48ff-81a9-b2a7e9c8730a","5ae4d15b-56f4-459b-bb8a-81804676ce42","8037f38c-d5ca-41a9-b347-a2e3edce6bb0","2084e267-b130-46dd-a324-d9d4a002fe84","5a046903-9590-40cb-9760-e46697c492f9","92802ab0-d132-432f-aa2d-87b41e00454a","bdafbc22-ebe6-43e7-a7a1-289c366f9b74","8307fc24-0ade-4ddf-ad3a-a6fcea5d93a6","73e2713f-62db-497e-b209-5f5e311398fe","793dc143-c0c4-4fb9-ad49-b4634dd95925","c669b4dc-3397-4ffa-831b-0c731022c116","d0ab3936-ef13-4808-b883-45c1f6d21a44","dd1944e5-d40e-4b56-bc3e-e541266d6490","7ae9ca44-af22-4905-9a4b-6428ea8f6e5e","0829f5c8-2e6c-489b-b136-de6ebaa7ef6b","9c282344-655e-45f8-adc1-7dd09b970210","853c4909-7dc7-4c74-bf90-1938499036c0","403f6610-5ceb-4d11-aef4-a65e279959aa","0cedc829-b078-46d5-b911-5110d2eaf0e8","b2f618bc-c0c2-4e13-9974-96b807b8c91d","ee70b1b1-ea54-4219-9a4b-5ce091234f6f","64e595c9-b413-4a89-b386-1981d7ce6b55","21eca9cc-9c2f-4ad2-adf7-af89b4f39a30","c7289ecc-5746-447b-8492-600a8e5ed5b3","d17c55f0-09c6-4ea9-9b88-e54370dd71c1","ec0cfb82-0877-42d5-91c3-6da2689f65e3","fb20c0a7-3a7f-4d05-87aa-f4b72c852473","d2025f50-d778-41c3-8f0e-40ec00ca03d7","755c247c-561f-4757-8be7-1eb12e9e0013","5f9b36ad-1ac5-4f81-a9ad-6fb57f82b9ae","515a685c-fc8d-47da-982b-81a1a06e6f4b"],"benchmarkVersion":"4-enterprise-search-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Recommendation-prompt presenceRecommendation presence · observed Sep 15, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"enterprise-search-platforms-2026-07-27","runArtifactIds":["6f2c67bc-e104-4095-a6bd-25ae19947d22","bd7f7fee-6dc8-4cfa-9981-39b48f151400","bbc0d259-e343-4fc1-bd38-8c083189d22a","eee356de-14f9-4159-aeb9-1e69e5d6b294","e03c915c-ead1-44c4-96c1-a93363a6ef21","c03c2534-9e4c-48ff-81a9-b2a7e9c8730a","5ae4d15b-56f4-459b-bb8a-81804676ce42","8037f38c-d5ca-41a9-b347-a2e3edce6bb0","2084e267-b130-46dd-a324-d9d4a002fe84","5a046903-9590-40cb-9760-e46697c492f9","92802ab0-d132-432f-aa2d-87b41e00454a","bdafbc22-ebe6-43e7-a7a1-289c366f9b74","8307fc24-0ade-4ddf-ad3a-a6fcea5d93a6","73e2713f-62db-497e-b209-5f5e311398fe","793dc143-c0c4-4fb9-ad49-b4634dd95925","c669b4dc-3397-4ffa-831b-0c731022c116","d0ab3936-ef13-4808-b883-45c1f6d21a44","dd1944e5-d40e-4b56-bc3e-e541266d6490","7ae9ca44-af22-4905-9a4b-6428ea8f6e5e","0829f5c8-2e6c-489b-b136-de6ebaa7ef6b","9c282344-655e-45f8-adc1-7dd09b970210","853c4909-7dc7-4c74-bf90-1938499036c0","403f6610-5ceb-4d11-aef4-a65e279959aa","0cedc829-b078-46d5-b911-5110d2eaf0e8","b2f618bc-c0c2-4e13-9974-96b807b8c91d","ee70b1b1-ea54-4219-9a4b-5ce091234f6f","64e595c9-b413-4a89-b386-1981d7ce6b55","21eca9cc-9c2f-4ad2-adf7-af89b4f39a30","c7289ecc-5746-447b-8492-600a8e5ed5b3","d17c55f0-09c6-4ea9-9b88-e54370dd71c1","ec0cfb82-0877-42d5-91c3-6da2689f65e3","fb20c0a7-3a7f-4d05-87aa-f4b72c852473","d2025f50-d778-41c3-8f0e-40ec00ca03d7","755c247c-561f-4757-8be7-1eb12e9e0013","5f9b36ad-1ac5-4f81-a9ad-6fb57f82b9ae","515a685c-fc8d-47da-982b-81a1a06e6f4b"],"benchmarkVersion":"4-enterprise-search-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Gemini citation shareGemini brand citation share · observed Sep 15, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"enterprise-search-platforms-2026-07-27","runArtifactIds":["6f2c67bc-e104-4095-a6bd-25ae19947d22","bd7f7fee-6dc8-4cfa-9981-39b48f151400","bbc0d259-e343-4fc1-bd38-8c083189d22a","eee356de-14f9-4159-aeb9-1e69e5d6b294","e03c915c-ead1-44c4-96c1-a93363a6ef21","c03c2534-9e4c-48ff-81a9-b2a7e9c8730a","5ae4d15b-56f4-459b-bb8a-81804676ce42","8037f38c-d5ca-41a9-b347-a2e3edce6bb0","2084e267-b130-46dd-a324-d9d4a002fe84","5a046903-9590-40cb-9760-e46697c492f9","92802ab0-d132-432f-aa2d-87b41e00454a","bdafbc22-ebe6-43e7-a7a1-289c366f9b74","8307fc24-0ade-4ddf-ad3a-a6fcea5d93a6","73e2713f-62db-497e-b209-5f5e311398fe","793dc143-c0c4-4fb9-ad49-b4634dd95925","c669b4dc-3397-4ffa-831b-0c731022c116","d0ab3936-ef13-4808-b883-45c1f6d21a44","dd1944e5-d40e-4b56-bc3e-e541266d6490","7ae9ca44-af22-4905-9a4b-6428ea8f6e5e","0829f5c8-2e6c-489b-b136-de6ebaa7ef6b","9c282344-655e-45f8-adc1-7dd09b970210","853c4909-7dc7-4c74-bf90-1938499036c0","403f6610-5ceb-4d11-aef4-a65e279959aa","0cedc829-b078-46d5-b911-5110d2eaf0e8","b2f618bc-c0c2-4e13-9974-96b807b8c91d","ee70b1b1-ea54-4219-9a4b-5ce091234f6f","64e595c9-b413-4a89-b386-1981d7ce6b55","21eca9cc-9c2f-4ad2-adf7-af89b4f39a30","c7289ecc-5746-447b-8492-600a8e5ed5b3","d17c55f0-09c6-4ea9-9b88-e54370dd71c1","ec0cfb82-0877-42d5-91c3-6da2689f65e3","fb20c0a7-3a7f-4d05-87aa-f4b72c852473","d2025f50-d778-41c3-8f0e-40ec00ca03d7","755c247c-561f-4757-8be7-1eb12e9e0013","5f9b36ad-1ac5-4f81-a9ad-6fb57f82b9ae","515a685c-fc8d-47da-982b-81a1a06e6f4b"],"benchmarkVersion":"4-enterprise-search-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Gemini mention coverageGemini brand mention coverage · observed Sep 15, 2026, 12:00 AM UTC8.333 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"enterprise-search-platforms-2026-07-27","runArtifactIds":["6f2c67bc-e104-4095-a6bd-25ae19947d22","bd7f7fee-6dc8-4cfa-9981-39b48f151400","bbc0d259-e343-4fc1-bd38-8c083189d22a","eee356de-14f9-4159-aeb9-1e69e5d6b294","e03c915c-ead1-44c4-96c1-a93363a6ef21","c03c2534-9e4c-48ff-81a9-b2a7e9c8730a","5ae4d15b-56f4-459b-bb8a-81804676ce42","8037f38c-d5ca-41a9-b347-a2e3edce6bb0","2084e267-b130-46dd-a324-d9d4a002fe84","5a046903-9590-40cb-9760-e46697c492f9","92802ab0-d132-432f-aa2d-87b41e00454a","bdafbc22-ebe6-43e7-a7a1-289c366f9b74","8307fc24-0ade-4ddf-ad3a-a6fcea5d93a6","73e2713f-62db-497e-b209-5f5e311398fe","793dc143-c0c4-4fb9-ad49-b4634dd95925","c669b4dc-3397-4ffa-831b-0c731022c116","d0ab3936-ef13-4808-b883-45c1f6d21a44","dd1944e5-d40e-4b56-bc3e-e541266d6490","7ae9ca44-af22-4905-9a4b-6428ea8f6e5e","0829f5c8-2e6c-489b-b136-de6ebaa7ef6b","9c282344-655e-45f8-adc1-7dd09b970210","853c4909-7dc7-4c74-bf90-1938499036c0","403f6610-5ceb-4d11-aef4-a65e279959aa","0cedc829-b078-46d5-b911-5110d2eaf0e8","b2f618bc-c0c2-4e13-9974-96b807b8c91d","ee70b1b1-ea54-4219-9a4b-5ce091234f6f","64e595c9-b413-4a89-b386-1981d7ce6b55","21eca9cc-9c2f-4ad2-adf7-af89b4f39a30","c7289ecc-5746-447b-8492-600a8e5ed5b3","d17c55f0-09c6-4ea9-9b88-e54370dd71c1","ec0cfb82-0877-42d5-91c3-6da2689f65e3","fb20c0a7-3a7f-4d05-87aa-f4b72c852473","d2025f50-d778-41c3-8f0e-40ec00ca03d7","755c247c-561f-4757-8be7-1eb12e9e0013","5f9b36ad-1ac5-4f81-a9ad-6fb57f82b9ae","515a685c-fc8d-47da-982b-81a1a06e6f4b"],"benchmarkVersion":"4-enterprise-search-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
Gemini recommendation-prompt presenceGemini brand recommendation presence · observed Sep 15, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
OpenAI citation shareOpenAI brand citation share · observed Sep 15, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
{"corpusVersion":"enterprise-search-platforms-2026-07-27","runArtifactIds":["6f2c67bc-e104-4095-a6bd-25ae19947d22","bd7f7fee-6dc8-4cfa-9981-39b48f151400","bbc0d259-e343-4fc1-bd38-8c083189d22a","eee356de-14f9-4159-aeb9-1e69e5d6b294","e03c915c-ead1-44c4-96c1-a93363a6ef21","c03c2534-9e4c-48ff-81a9-b2a7e9c8730a","5ae4d15b-56f4-459b-bb8a-81804676ce42","8037f38c-d5ca-41a9-b347-a2e3edce6bb0","2084e267-b130-46dd-a324-d9d4a002fe84","5a046903-9590-40cb-9760-e46697c492f9","92802ab0-d132-432f-aa2d-87b41e00454a","bdafbc22-ebe6-43e7-a7a1-289c366f9b74","8307fc24-0ade-4ddf-ad3a-a6fcea5d93a6","73e2713f-62db-497e-b209-5f5e311398fe","793dc143-c0c4-4fb9-ad49-b4634dd95925","c669b4dc-3397-4ffa-831b-0c731022c116","d0ab3936-ef13-4808-b883-45c1f6d21a44","dd1944e5-d40e-4b56-bc3e-e541266d6490","7ae9ca44-af22-4905-9a4b-6428ea8f6e5e","0829f5c8-2e6c-489b-b136-de6ebaa7ef6b","9c282344-655e-45f8-adc1-7dd09b970210","853c4909-7dc7-4c74-bf90-1938499036c0","403f6610-5ceb-4d11-aef4-a65e279959aa","0cedc829-b078-46d5-b911-5110d2eaf0e8","b2f618bc-c0c2-4e13-9974-96b807b8c91d","ee70b1b1-ea54-4219-9a4b-5ce091234f6f","64e595c9-b413-4a89-b386-1981d7ce6b55","21eca9cc-9c2f-4ad2-adf7-af89b4f39a30","c7289ecc-5746-447b-8492-600a8e5ed5b3","d17c55f0-09c6-4ea9-9b88-e54370dd71c1","ec0cfb82-0877-42d5-91c3-6da2689f65e3","fb20c0a7-3a7f-4d05-87aa-f4b72c852473","d2025f50-d778-41c3-8f0e-40ec00ca03d7","755c247c-561f-4757-8be7-1eb12e9e0013","5f9b36ad-1ac5-4f81-a9ad-6fb57f82b9ae","515a685c-fc8d-47da-982b-81a1a06e6f4b"],"benchmarkVersion":"4-enterprise-search-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Open the source
OpenAI mention coverageOpenAI brand mention coverage · observed Sep 15, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source
OpenAI recommendation-prompt presenceOpenAI brand recommendation presence · observed Sep 15, 2026, 12:00 AM UTC0 percent100% confidence
Source
Rank.ai Enterprise Search Prompt Benchmark
Grade
A
Freshness
fresh
Locator
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Open the source

Cite this data

Free to use with attribution. Copy a citation, or link to this page: it keeps its address when the board updates.

Plain textEnterprise search platform rank. Rank.ai, data as of September 15, 2026. https://www.rank.ai/rankings/enterprise-search/enterprise-search-platform-brand-rank
HTML<a href="https://www.rank.ai/rankings/enterprise-search/enterprise-search-platform-brand-rank">Enterprise search platform rank</a>, Rank.ai, data as of September 15, 2026
Markdown[Enterprise search platform rank](https://www.rank.ai/rankings/enterprise-search/enterprise-search-platform-brand-rank), Rank.ai, data as of September 15, 2026
APARank.ai. (2026). Enterprise search platform rank. Retrieved October 22, 2026, from https://www.rank.ai/rankings/enterprise-search/enterprise-search-platform-brand-rank

Embed this table

Paste this on your site. It shows the latest published snapshot, and the credit line links readers to the full ranking.

<iframe src="https://www.rank.ai/embed/boards/enterprise-search-platform-brand-rank" title="Enterprise search platform rank" width="100%" height="420" loading="lazy" style="border:1px solid #111;max-width:720px"></iframe>
<p style="font-size:12px">Source: <a href="https://www.rank.ai/rankings/enterprise-search/enterprise-search-platform-brand-rank">Enterprise search platform rank</a> by Rank.ai</p>

More in Enterprise search & RAG

Workplace search, managed retrieval, and grounded knowledge platforms ranked across a fixed enterprise buying corpus, with brand, prompt, engine and citation source views.

3 boards

Enterprise search platform presence

Reviewed platforms ranked by the share of all the category's answers that name or cite them.

1Elastic Search AI138.9%
2GoSearch230.6%
3Glean230.6%

Enterprise search citation share

Reviewed platforms ranked by distinct answer-level citations to their canonical domains.

1GoSearch132.3%
2Glean122.6%
3Onyx AI116.1%

Enterprise search engine breadth

Reviewed platforms ranked by how many of the three model APIs name or cite them.

1Elastic Search AI13 engines
2Onyx AI43 engines
3Azure AI Search3 engines

Enterprise search platform presence

Reviewed platforms ranked by the share of all the category's answers that name or cite them.

Enterprise search citation share

Reviewed platforms ranked by distinct answer-level citations to their canonical domains.

Enterprise search engine breadth

Reviewed platforms ranked by how many of the three model APIs name or cite them.

See how often AI names you.

Enter your website. In about two minutes, Rank.ai asks ChatGPT, Claude and Gemini 12 questions your customers ask and grades how often they name you.

Your grade out of 100How often AI names you, cites your site, and how high it ranks you.
Who gets namedEvery competitor in the answers, most named first.
The pages AI readsThe sources behind each answer.
Three fixesWhat to fix first, with a brief for the first article.

Enterprise search platform rank

All 16 companies by recommendation prompt presence

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite

Algolia on Enterprise Search Platform Rank

What the score is built from

Moved up since the previous snapshot

Where each number comes from

More in Enterprise search & RAG

See how often AI names you.

One brand against up to three competitors, answer by answer

Which compared brands each answer names

The sites these answers cite