AI Rankings · ai and machine learning platforms · Australia
Amazon SageMaker Model Governance & Clarify, according to AI (October 2026)
When a buyer in Australia asked ChatGPT, Gemini or Google AI Mode for AI and machine learning platforms, Amazon SageMaker Model Governance & Clarify came up in 14 of 180 answers. That puts it #8 of the 315 companies AI named in Australia.
In 13 of those 14 answers AI recommended it. In the other one it only mentioned it.
- 60 buyer questions
- 180 answers read
- 3 engines
Where you stand
Your totals across all 3 engines first, then the same numbers engine by engine. Rank is your place among the companies that engine named in Australia. Mention rate is the share of that engine’s answers that name you. Recommendation rate is the share of your mentions where you are put forward as a recommendation, not just named. Average position is the place you take in an answer that names you, 1 means first. Questions you appear in is how many of the 60 buyer questions named you at least once.
| Engine | Rank | Mention rate | Recommendation rate | Average position | Questions you appear in |
|---|---|---|---|---|---|
| All 3 engines | #8of 315 | 8% | 93% | 4.5 | 9 of 60 |
 ChatGPT | #6of 169 | 8% | 80% | 6.8 | 5 of 60 |
 Gemini | #12of 147 | 7% | 100% | 4.0 | 4 of 60 |
 Google AI Mode | #8of 127 | 8% | 100% | 2.6 | 5 of 60 |
ChatGPT names Amazon SageMaker Model Governance & Clarify most often, Gemini least. Microsoft Azure leads on all 3 engines.
Named instead of you
The leader, the three named right above you, and you. Share of answers that name each one, overall and on each engine.
| Rank | company | Mention rate | ChatGPT | Gemini | Google AI Mode |
|---|---|---|---|---|---|
| 1 | Microsoft Azure48 answers ahead of you | 36% | 32% | 38% | 33% |
| 5 | OpenAI5 answers ahead of you | 11% | 10% | 12% | 10% |
| 6 | MLflow2 answers ahead of you | 9% | 7% | 10% | 10% |
| 7 | Anthropic1 answer ahead of you | 8% | 7% | 8% | 10% |
| 8 | Amazon SageMaker Model Governance & Clarifyyou | 8% | 8% | 7% | 8% |
Anthropic is 1 answer ahead of you, Dataiku 1 behind.
See, question by question, who took the spot →In AI’s own words
How the engines described Amazon SageMaker Model Governance & Clarify when they named it, word for word, from the October 2026 answers.
Databricks explicitly supports telecom churn use cases. [1] Amazon SageMaker — a strong alternative if your telco is heavily AWS-based
SageMaker Pipelines can orchestrate preprocessing → training → evaluation → deployment, and AWS has specific reference architecture for subscriber churn using CDR, billing and customer-care data.
A fully managed AWS service purpose-built for end-to-end MLOps.
AI states 22 facts about Amazon SageMaker Model Governance & Clarify
In the October 2026 answers, AI describes your company in 22 statements: 19 about the service, 2 about other things and 1 about address.
Findrix checks each one against your own facts, statement by statement, and writes the correction email for you.
Check all 22 in Findrix →What to do with this report
Get named where you are not
Amazon SageMaker Model Governance & Clarify appeared in 9 of the 60 buyer questions. Findrix runs the other 51 for you and shows who AI names there instead, and which sites got them the spot.
Fix what AI gets wrong
AI states 22 facts about Amazon SageMaker Model Governance & Clarify. Findrix puts each one next to your own facts and writes the correction email for you to send.
Watch it move
In your inbox: a report after every scan and a monthly PDF for your team. An email when a fix worked or a rival overtakes you, and right away if your site blocks AI bots or goes down.
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