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 engine breadth
12 companies ranked by how many AI engines name them.
3 engines
Fivetran ranks first
Engine breadth
12
Companies ranked
Sep 22
Snapshot recorded
2026 · Rotating schedule
3
Answers behind each row
From the OpenAI, Anthropic and Google model APIs
All 12 companies by engine breadth
Fivetran leads at 3 engines; the middle of the board sits at 2.
- Ahead of second place
- 0
- Held by the top three
- 38%
- Middle of the board
- 2
- Below half the leader
- 2 of 12
Rank, name and engine breadthMiddle 2
- 1Fivetran3 engines
- 2Airbyte3 engines
- 3Qlik Talend3 engines
- 4Hevo Data2 engines
- 5Matillion2 engines
- 6Informatica2 engines
- 7Estuary Flow2 engines
- 8MuleSoft2 engines
- 9Boomi2 engines
- 10SnapLogic2 engines
- 11Hightouch1 engines
- 12Census0 engines
engines: 2 on 7 of 12 rows · 3 checks behind each row · 100% confidence across rows.
| Rank | Name | Engine breadth | Mention coverage | Share of names | Cited as source | Change | Why |
|---|---|---|---|---|---|---|---|
| 01 | Fivetran | 3 engines | 37.5% · 18 / 48 | 25.35% · 18 / 71 | 30% · 9 / 30 | This rankMy rank | |
| 02 | Airbyte | 3 engines | 18.75% · 9 / 48 | 12.68% · 9 / 71 | 13.33% · 4 / 30 | This rankMy rank | |
| 03 | Qlik Talend | 3 engines | 20.83% · 10 / 48 | 14.08% · 10 / 71 | 6.67% · 2 / 30 | This rankMy rank | |
| 04 | Hevo Data | 2 engines | 14.58% · 7 / 48 | 9.86% · 7 / 71 | 10% · 3 / 30 | 5 | This rankMy rank |
| 05 | Matillion | 2 engines | 12.5% · 6 / 48 | 8.45% · 6 / 71 | 10% · 3 / 30 | 1 | This rankMy rank |
| 06 | Informatica | 2 engines | 10.42% · 5 / 48 | 7.04% · 5 / 71 | 0% · 0 / 30 | 1 | This rankMy rank |
| 07 | Estuary Flow | 2 engines | 12.5% · 6 / 48 | 8.45% · 6 / 71 | 16.67% · 5 / 30 | This rankMy rank | |
| 08 | MuleSoft | 2 engines | 8.33% · 4 / 48 | 5.63% · 4 / 71 | 0% · 0 / 30 | 4 | ShowingMy rank |
| 09 | Boomi | 2 engines | 6.25% · 3 / 48 | 4.23% · 3 / 71 | 6.67% · 2 / 30 | 3 | This rankMy rank |
| 10 | SnapLogic | 2 engines | 4.17% · 2 / 48 | 2.82% · 2 / 71 | 3.33% · 1 / 30 | 2 | This rankMy rank |
| 11 | Hightouch | 1 engines | 2.08% · 1 / 48 | 1.41% · 1 / 71 | 3.33% · 1 / 30 | This rankMy rank | |
| 12 | Census | 0 engines | 0% · 0 / 48 | 0% · 0 / 71 | 0% · 0 / 30 | 2 | This rankMy rank |
Why this rank
MuleSoft on Data Integration Engine Breadth
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.
8
Rank on this board
2 engines
Score
3
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 |
|---|---|---|
| Engine breadth | 2 | 2 |
Moved up since the previous snapshot
+4 places- Gemini brand mention coverage0 to 12.5+12.5
- Gemini brand recommendation presence0 to 12.5+12.5
- OpenAI brand mention coverage0 to 12.5+12.5
- OpenAI brand recommendation presence0 to 12.5+12.5
- Mention coverage0 to 8.333+8.333
- Recommendation presence0 to 8.333+8.333
- Mention share0 to 5.634+5.634
- Engine breadth0 to 2+2
- Anthropic brand mention coverage0 to 00
- Anthropic brand recommendation presence0 to 00
- Citation share0 to 00
- Gemini brand citation share0 to 00
- OpenAI brand citation share0 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 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"}
Engine breadthEngine breadth · observed Sep 22, 2026, 12:00 AM UTC2 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 UTC8.333 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"}
Reviewed-brand presence shareMention share · observed Sep 22, 2026, 12:00 AM UTC5.634 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 UTC8.333 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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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
- Freshness
- fresh
- Locator
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Gemini mention coverageGemini brand mention coverage · observed Sep 22, 2026, 12:00 AM UTC12.5 percent100% confidence
- Source
- Rank.ai Data Integration Prompt Benchmark
- Grade
- A
- Freshness
- fresh
- Locator
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Gemini recommendation-prompt presenceGemini brand recommendation presence · observed Sep 22, 2026, 12:00 AM UTC12.5 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 UTC0 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 UTC12.5 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 UTC12.5 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.