Reviewed integration platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.
Data integration
Data integration brands in Gemini model API answers
12 companies ranked by how often Google's Gemini model API names or cites them.
75.0%
Fivetran ranks first
Gemini recommendation prompt presence
12
Companies ranked
Sep 22
Snapshot recorded
2026 · Rotating schedule
8
Answers behind each row
From the OpenAI, Anthropic and Google model APIs
All 12 companies by gemini recommendation prompt presence
Fivetran leads at 75.0%; the middle of the board sits at 12.5%.
- Ahead of second place
- 12.5%
- Held by the top three
- 67%
- Middle of the board
- 12.5%
- Below half the leader
- 9 of 12
Rank, name and gemini recommendation prompt presenceMiddle 12.5%
- 1Fivetran75.0%
- 2Airbyte62.5%
- 3Qlik Talend37.5%
- 4Hevo Data25.0%
- 5Matillion12.5%
- 6Informatica12.5%
- 7Estuary Flow12.5%
- 8MuleSoft12.5%
- 9Boomi12.5%
- 10SnapLogic0.0%
- 11Hightouch0.0%
- 12Census0.0%
engines: 2 on 7 of 12 rows · 8 checks behind each row · 100% confidence across rows.
| Rank | Name | Gemini recommendation prompt presence | Mention coverage | Share of names | Cited as source | Change | Why |
|---|---|---|---|---|---|---|---|
| 01 | Fivetran | 75.0% | 37.5% · 18 / 48 | 25.35% · 18 / 71 | 30% · 9 / 30 | This rankMy rank | |
| 02 | Airbyte | 62.5% | 18.75% · 9 / 48 | 12.68% · 9 / 71 | 13.33% · 4 / 30 | This rankMy rank | |
| 03 | Qlik Talend | 37.5% | 20.83% · 10 / 48 | 14.08% · 10 / 71 | 6.67% · 2 / 30 | 4 | This rankMy rank |
| 04 | Hevo Data | 25.0% | 14.58% · 7 / 48 | 9.86% · 7 / 71 | 10% · 3 / 30 | This rankMy rank | |
| 05 | Matillion | 12.5% | 12.5% · 6 / 48 | 8.45% · 6 / 71 | 10% · 3 / 30 | 2 | This rankMy rank |
| 06 | Informatica | 12.5% | 10.42% · 5 / 48 | 7.04% · 5 / 71 | 0% · 0 / 30 | 2 | This rankMy rank |
| 07 | Estuary Flow | 12.5% | 12.5% · 6 / 48 | 8.45% · 6 / 71 | 16.67% · 5 / 30 | 3 | This rankMy rank |
| 08 | MuleSoft | 12.5% | 8.33% · 4 / 48 | 5.63% · 4 / 71 | 0% · 0 / 30 | 4 | This rankMy rank |
| 09 | Boomi | 12.5% | 6.25% · 3 / 48 | 4.23% · 3 / 71 | 6.67% · 2 / 30 | This rankMy rank | |
| 10 | SnapLogic | 0.0% | 4.17% · 2 / 48 | 2.82% · 2 / 71 | 3.33% · 1 / 30 | 1 | This rankMy rank |
| 11 | Hightouch | 0.0% | 2.08% · 1 / 48 | 1.41% · 1 / 71 | 3.33% · 1 / 30 | 5 | ShowingMy rank |
| 12 | Census | 0.0% | 0% · 0 / 48 | 0% · 0 / 71 | 0% · 0 / 30 | 7 | This rankMy rank |
Why this rank
Hightouch on Data Integration Brands in Gemini Model API Answers
Snapshot of Sep 22, 2026, 12:00 AM UTC · Link to this snapshot
Ranks a reviewed Data Integration brand universe using a fixed, public set of neutral commercial prompts across 3 AI providers.
11
Rank on this board
0 percent
Score
8
Answers behind the score
100% confidence · 1 of 1 components evidenced
What the score is built from
1 of 1 evidencedEvery component evidenced · 1 evidence record each
| Component | Value | Contribution |
|---|---|---|
| Gemini brand recommendation presence | 0 | 0 |
Moved down since the previous snapshot
-5 places- Gemini brand recommendation presence12.5 to 0-12.5
- Gemini brand mention coverage6.25 to 0-6.25
- OpenAI brand mention coverage0 to 6.25+6.25
- OpenAI brand citation share0 to 5.882+5.882
- Recommendation presence4.167 to 0-4.167
- Citation share0 to 3.333+3.333
- Mention share1.724 to 1.408-0.316
- Anthropic brand mention coverage0 to 00
- Anthropic brand recommendation presence0 to 00
- Engine breadth1 to 10
- Mention coverage2.083 to 2.0830
- Gemini brand citation share0 to 00
- OpenAI brand recommendation presence0 to 00
Where each number comes from
13 public recordsAnthropic mention coverageAnthropic brand mention coverage · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
{"corpusVersion":"data-integration-platforms-2026-07-27","runArtifactIds":["7ce7c4bd-4951-443d-87a4-34707db586bb","f93f176f-5c88-4116-991a-976c8a62aade","24f5964f-bd26-43c4-b39f-7321214dc87c","877df6fd-4fe4-4218-ad4a-b062f9b2243d","a3491061-2e9f-4950-b9b0-b22d5045ea8b","355997c8-c95f-4f90-a8d1-892e532d5076","82bb7da5-36f9-4d8a-a980-d4ed27d3d062","e481535f-b02a-456f-a4df-c5914f65c14d","1af7065b-2487-402e-b884-2cb7fbfdd313","019709d6-25bd-4000-988a-b4588b4e2ba5","169a85f4-d55a-40ae-813a-bb02e61d920e","e465dbbc-2f69-4bc9-89a0-8507d6f42c84","8cd16adc-b811-44e5-a7d4-8060004ded0c","c0b8b8c4-d3f7-45cc-bdef-e06ff9c643c1","6a60171b-77ff-4cfd-b5b0-6c73d29f85b5","89811e81-3d66-46df-866f-35f3a797c861","63897b24-cc86-4efc-b5b3-90b62257a5b1","62295d9e-31ea-47ba-9801-e9aef566c308","251ca83f-e0cf-4d48-80f4-47069f1eac4b","f8a71c95-7155-4b0b-a624-0449580dc2f4","5b4004b3-9d5d-4b55-9d39-dfc0ba9f3af9","0e9e9191-e1a7-4d47-b592-1c6d159b9089","fe29cd73-e0b1-4581-8922-8e262293f6df","228b0773-ffa1-41b0-8b52-a031ec6dd57a","fb3b81e9-9242-4f57-9d64-acbc0c350e4b","aaf86a5d-af65-4839-a7c8-6bf62af069d8","bd2351cd-22a1-48dd-a3d6-878f4f0598dc","710819c0-f258-41de-aa65-03ee3a80a3ea","ef164e28-6cfc-4bc2-8096-fabbf143bc6f","f82d658d-a3f0-4929-9ab6-81d7e73cc97d","3601253b-2dcd-4d91-abbe-d76a68ad21e2","cbcadb32-8c9f-4134-9076-abc2b993a55e","f2b33f07-a6b4-4edb-a291-924b8430390c","c77c5810-2b89-45fe-9a4d-64fdb0456f45","e9a96b4e-f4a1-40f2-a184-9ff0b397bcda","e69ceb6a-00e8-487c-9dad-791ec7db1fab","091ff6fe-b848-413e-b54a-db2268dea07f","b70c45d6-68c3-423c-b9bb-95fec9b3c804","8ce1560e-ba6f-4978-8b36-d0151674d901","bd7aa6c0-7b9a-474a-9bc3-a3cde122a5d8","37076ce0-2f00-48d6-b7fe-d433e79b5d50","31342e7c-71dc-4ee6-97b7-9e439846de2f","811caa35-c802-465e-ae82-71799d42ac39","eaf9c5a1-c453-4331-bbd0-ff1ca1487adb","1987e9a8-e750-4860-8a76-238cdae27b14","1ba7ab34-36f4-4996-b894-4854d89755b0","9d667376-0ace-4049-8463-3988e351e41b","4837c5a2-c74e-4a7f-84ae-a1906fe91563"],"benchmarkVersion":"4-data-integration-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Anthropic recommendation-prompt presenceAnthropic brand recommendation presence · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
{"corpusVersion":"data-integration-platforms-2026-07-27","runArtifactIds":["7ce7c4bd-4951-443d-87a4-34707db586bb","f93f176f-5c88-4116-991a-976c8a62aade","24f5964f-bd26-43c4-b39f-7321214dc87c","877df6fd-4fe4-4218-ad4a-b062f9b2243d","a3491061-2e9f-4950-b9b0-b22d5045ea8b","355997c8-c95f-4f90-a8d1-892e532d5076","82bb7da5-36f9-4d8a-a980-d4ed27d3d062","e481535f-b02a-456f-a4df-c5914f65c14d","1af7065b-2487-402e-b884-2cb7fbfdd313","019709d6-25bd-4000-988a-b4588b4e2ba5","169a85f4-d55a-40ae-813a-bb02e61d920e","e465dbbc-2f69-4bc9-89a0-8507d6f42c84","8cd16adc-b811-44e5-a7d4-8060004ded0c","c0b8b8c4-d3f7-45cc-bdef-e06ff9c643c1","6a60171b-77ff-4cfd-b5b0-6c73d29f85b5","89811e81-3d66-46df-866f-35f3a797c861","63897b24-cc86-4efc-b5b3-90b62257a5b1","62295d9e-31ea-47ba-9801-e9aef566c308","251ca83f-e0cf-4d48-80f4-47069f1eac4b","f8a71c95-7155-4b0b-a624-0449580dc2f4","5b4004b3-9d5d-4b55-9d39-dfc0ba9f3af9","0e9e9191-e1a7-4d47-b592-1c6d159b9089","fe29cd73-e0b1-4581-8922-8e262293f6df","228b0773-ffa1-41b0-8b52-a031ec6dd57a","fb3b81e9-9242-4f57-9d64-acbc0c350e4b","aaf86a5d-af65-4839-a7c8-6bf62af069d8","bd2351cd-22a1-48dd-a3d6-878f4f0598dc","710819c0-f258-41de-aa65-03ee3a80a3ea","ef164e28-6cfc-4bc2-8096-fabbf143bc6f","f82d658d-a3f0-4929-9ab6-81d7e73cc97d","3601253b-2dcd-4d91-abbe-d76a68ad21e2","cbcadb32-8c9f-4134-9076-abc2b993a55e","f2b33f07-a6b4-4edb-a291-924b8430390c","c77c5810-2b89-45fe-9a4d-64fdb0456f45","e9a96b4e-f4a1-40f2-a184-9ff0b397bcda","e69ceb6a-00e8-487c-9dad-791ec7db1fab","091ff6fe-b848-413e-b54a-db2268dea07f","b70c45d6-68c3-423c-b9bb-95fec9b3c804","8ce1560e-ba6f-4978-8b36-d0151674d901","bd7aa6c0-7b9a-474a-9bc3-a3cde122a5d8","37076ce0-2f00-48d6-b7fe-d433e79b5d50","31342e7c-71dc-4ee6-97b7-9e439846de2f","811caa35-c802-465e-ae82-71799d42ac39","eaf9c5a1-c453-4331-bbd0-ff1ca1487adb","1987e9a8-e750-4860-8a76-238cdae27b14","1ba7ab34-36f4-4996-b894-4854d89755b0","9d667376-0ace-4049-8463-3988e351e41b","4837c5a2-c74e-4a7f-84ae-a1906fe91563"],"benchmarkVersion":"4-data-integration-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Citation shareCitation share · observed Sep 22, 2026, 12:00 AM UTC3.333 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
{"corpusVersion":"data-integration-platforms-2026-07-27","runArtifactIds":["7ce7c4bd-4951-443d-87a4-34707db586bb","f93f176f-5c88-4116-991a-976c8a62aade","24f5964f-bd26-43c4-b39f-7321214dc87c","877df6fd-4fe4-4218-ad4a-b062f9b2243d","a3491061-2e9f-4950-b9b0-b22d5045ea8b","355997c8-c95f-4f90-a8d1-892e532d5076","82bb7da5-36f9-4d8a-a980-d4ed27d3d062","e481535f-b02a-456f-a4df-c5914f65c14d","1af7065b-2487-402e-b884-2cb7fbfdd313","019709d6-25bd-4000-988a-b4588b4e2ba5","169a85f4-d55a-40ae-813a-bb02e61d920e","e465dbbc-2f69-4bc9-89a0-8507d6f42c84","8cd16adc-b811-44e5-a7d4-8060004ded0c","c0b8b8c4-d3f7-45cc-bdef-e06ff9c643c1","6a60171b-77ff-4cfd-b5b0-6c73d29f85b5","89811e81-3d66-46df-866f-35f3a797c861","63897b24-cc86-4efc-b5b3-90b62257a5b1","62295d9e-31ea-47ba-9801-e9aef566c308","251ca83f-e0cf-4d48-80f4-47069f1eac4b","f8a71c95-7155-4b0b-a624-0449580dc2f4","5b4004b3-9d5d-4b55-9d39-dfc0ba9f3af9","0e9e9191-e1a7-4d47-b592-1c6d159b9089","fe29cd73-e0b1-4581-8922-8e262293f6df","228b0773-ffa1-41b0-8b52-a031ec6dd57a","fb3b81e9-9242-4f57-9d64-acbc0c350e4b","aaf86a5d-af65-4839-a7c8-6bf62af069d8","bd2351cd-22a1-48dd-a3d6-878f4f0598dc","710819c0-f258-41de-aa65-03ee3a80a3ea","ef164e28-6cfc-4bc2-8096-fabbf143bc6f","f82d658d-a3f0-4929-9ab6-81d7e73cc97d","3601253b-2dcd-4d91-abbe-d76a68ad21e2","cbcadb32-8c9f-4134-9076-abc2b993a55e","f2b33f07-a6b4-4edb-a291-924b8430390c","c77c5810-2b89-45fe-9a4d-64fdb0456f45","e9a96b4e-f4a1-40f2-a184-9ff0b397bcda","e69ceb6a-00e8-487c-9dad-791ec7db1fab","091ff6fe-b848-413e-b54a-db2268dea07f","b70c45d6-68c3-423c-b9bb-95fec9b3c804","8ce1560e-ba6f-4978-8b36-d0151674d901","bd7aa6c0-7b9a-474a-9bc3-a3cde122a5d8","37076ce0-2f00-48d6-b7fe-d433e79b5d50","31342e7c-71dc-4ee6-97b7-9e439846de2f","811caa35-c802-465e-ae82-71799d42ac39","eaf9c5a1-c453-4331-bbd0-ff1ca1487adb","1987e9a8-e750-4860-8a76-238cdae27b14","1ba7ab34-36f4-4996-b894-4854d89755b0","9d667376-0ace-4049-8463-3988e351e41b","4837c5a2-c74e-4a7f-84ae-a1906fe91563"],"benchmarkVersion":"4-data-integration-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Engine breadthEngine breadth · observed Sep 22, 2026, 12:00 AM UTC1 engines100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
{"corpusVersion":"data-integration-platforms-2026-07-27","runArtifactIds":["7ce7c4bd-4951-443d-87a4-34707db586bb","f93f176f-5c88-4116-991a-976c8a62aade","24f5964f-bd26-43c4-b39f-7321214dc87c","877df6fd-4fe4-4218-ad4a-b062f9b2243d","a3491061-2e9f-4950-b9b0-b22d5045ea8b","355997c8-c95f-4f90-a8d1-892e532d5076","82bb7da5-36f9-4d8a-a980-d4ed27d3d062","e481535f-b02a-456f-a4df-c5914f65c14d","1af7065b-2487-402e-b884-2cb7fbfdd313","019709d6-25bd-4000-988a-b4588b4e2ba5","169a85f4-d55a-40ae-813a-bb02e61d920e","e465dbbc-2f69-4bc9-89a0-8507d6f42c84","8cd16adc-b811-44e5-a7d4-8060004ded0c","c0b8b8c4-d3f7-45cc-bdef-e06ff9c643c1","6a60171b-77ff-4cfd-b5b0-6c73d29f85b5","89811e81-3d66-46df-866f-35f3a797c861","63897b24-cc86-4efc-b5b3-90b62257a5b1","62295d9e-31ea-47ba-9801-e9aef566c308","251ca83f-e0cf-4d48-80f4-47069f1eac4b","f8a71c95-7155-4b0b-a624-0449580dc2f4","5b4004b3-9d5d-4b55-9d39-dfc0ba9f3af9","0e9e9191-e1a7-4d47-b592-1c6d159b9089","fe29cd73-e0b1-4581-8922-8e262293f6df","228b0773-ffa1-41b0-8b52-a031ec6dd57a","fb3b81e9-9242-4f57-9d64-acbc0c350e4b","aaf86a5d-af65-4839-a7c8-6bf62af069d8","bd2351cd-22a1-48dd-a3d6-878f4f0598dc","710819c0-f258-41de-aa65-03ee3a80a3ea","ef164e28-6cfc-4bc2-8096-fabbf143bc6f","f82d658d-a3f0-4929-9ab6-81d7e73cc97d","3601253b-2dcd-4d91-abbe-d76a68ad21e2","cbcadb32-8c9f-4134-9076-abc2b993a55e","f2b33f07-a6b4-4edb-a291-924b8430390c","c77c5810-2b89-45fe-9a4d-64fdb0456f45","e9a96b4e-f4a1-40f2-a184-9ff0b397bcda","e69ceb6a-00e8-487c-9dad-791ec7db1fab","091ff6fe-b848-413e-b54a-db2268dea07f","b70c45d6-68c3-423c-b9bb-95fec9b3c804","8ce1560e-ba6f-4978-8b36-d0151674d901","bd7aa6c0-7b9a-474a-9bc3-a3cde122a5d8","37076ce0-2f00-48d6-b7fe-d433e79b5d50","31342e7c-71dc-4ee6-97b7-9e439846de2f","811caa35-c802-465e-ae82-71799d42ac39","eaf9c5a1-c453-4331-bbd0-ff1ca1487adb","1987e9a8-e750-4860-8a76-238cdae27b14","1ba7ab34-36f4-4996-b894-4854d89755b0","9d667376-0ace-4049-8463-3988e351e41b","4837c5a2-c74e-4a7f-84ae-a1906fe91563"],"benchmarkVersion":"4-data-integration-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Mention coverageMention coverage · observed Sep 22, 2026, 12:00 AM UTC2.083 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
{"corpusVersion":"data-integration-platforms-2026-07-27","runArtifactIds":["7ce7c4bd-4951-443d-87a4-34707db586bb","f93f176f-5c88-4116-991a-976c8a62aade","24f5964f-bd26-43c4-b39f-7321214dc87c","877df6fd-4fe4-4218-ad4a-b062f9b2243d","a3491061-2e9f-4950-b9b0-b22d5045ea8b","355997c8-c95f-4f90-a8d1-892e532d5076","82bb7da5-36f9-4d8a-a980-d4ed27d3d062","e481535f-b02a-456f-a4df-c5914f65c14d","1af7065b-2487-402e-b884-2cb7fbfdd313","019709d6-25bd-4000-988a-b4588b4e2ba5","169a85f4-d55a-40ae-813a-bb02e61d920e","e465dbbc-2f69-4bc9-89a0-8507d6f42c84","8cd16adc-b811-44e5-a7d4-8060004ded0c","c0b8b8c4-d3f7-45cc-bdef-e06ff9c643c1","6a60171b-77ff-4cfd-b5b0-6c73d29f85b5","89811e81-3d66-46df-866f-35f3a797c861","63897b24-cc86-4efc-b5b3-90b62257a5b1","62295d9e-31ea-47ba-9801-e9aef566c308","251ca83f-e0cf-4d48-80f4-47069f1eac4b","f8a71c95-7155-4b0b-a624-0449580dc2f4","5b4004b3-9d5d-4b55-9d39-dfc0ba9f3af9","0e9e9191-e1a7-4d47-b592-1c6d159b9089","fe29cd73-e0b1-4581-8922-8e262293f6df","228b0773-ffa1-41b0-8b52-a031ec6dd57a","fb3b81e9-9242-4f57-9d64-acbc0c350e4b","aaf86a5d-af65-4839-a7c8-6bf62af069d8","bd2351cd-22a1-48dd-a3d6-878f4f0598dc","710819c0-f258-41de-aa65-03ee3a80a3ea","ef164e28-6cfc-4bc2-8096-fabbf143bc6f","f82d658d-a3f0-4929-9ab6-81d7e73cc97d","3601253b-2dcd-4d91-abbe-d76a68ad21e2","cbcadb32-8c9f-4134-9076-abc2b993a55e","f2b33f07-a6b4-4edb-a291-924b8430390c","c77c5810-2b89-45fe-9a4d-64fdb0456f45","e9a96b4e-f4a1-40f2-a184-9ff0b397bcda","e69ceb6a-00e8-487c-9dad-791ec7db1fab","091ff6fe-b848-413e-b54a-db2268dea07f","b70c45d6-68c3-423c-b9bb-95fec9b3c804","8ce1560e-ba6f-4978-8b36-d0151674d901","bd7aa6c0-7b9a-474a-9bc3-a3cde122a5d8","37076ce0-2f00-48d6-b7fe-d433e79b5d50","31342e7c-71dc-4ee6-97b7-9e439846de2f","811caa35-c802-465e-ae82-71799d42ac39","eaf9c5a1-c453-4331-bbd0-ff1ca1487adb","1987e9a8-e750-4860-8a76-238cdae27b14","1ba7ab34-36f4-4996-b894-4854d89755b0","9d667376-0ace-4049-8463-3988e351e41b","4837c5a2-c74e-4a7f-84ae-a1906fe91563"],"benchmarkVersion":"4-data-integration-platforms-2026-07-27-models-64232fd32583","providerMatrixVersion":"64232fd32583"}
Reviewed-brand presence shareMention share · observed Sep 22, 2026, 12:00 AM UTC1.408 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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Recommendation-prompt presenceRecommendation presence · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
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Gemini citation shareGemini brand citation share · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
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- fresh
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Gemini mention coverageGemini brand mention coverage · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
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- fresh
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Gemini recommendation-prompt presenceGemini brand recommendation presence · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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OpenAI citation shareOpenAI brand citation share · observed Sep 22, 2026, 12:00 AM UTC5.882 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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OpenAI mention coverageOpenAI brand mention coverage · observed Sep 22, 2026, 12:00 AM UTC6.25 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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OpenAI recommendation-prompt presenceOpenAI brand recommendation presence · observed Sep 22, 2026, 12:00 AM UTC0 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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More in Data integration
Ingestion, ELT, CDC, integration, and data activation platforms ranked across a fixed enterprise buying corpus.
Reviewed vendors ranked by the share of all the category's answers that name or cite them.
Reviewed vendors ranked by their share of the citations that point to vendor websites.
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.