Compare
Vertex AI Training, Azure AI Search, Azure Machine Learning vs Amazon SageMaker Training
Every row below is computed for the brief in section 01. Nothing here is a universal score.
- Source
- Registry and rules engines over one brief, 8 cells anchored in 9 fetched records
- Verified
- 20 Sep 2026
- Confidence
- Medium
01The brief this answers
No context was supplied, so this is a generic reading. Every figure below would move for a real brief.
The same tool can score differently for a different brief.
- Objective
- Choosing a cloud platform
- Also
- Prediction from operational data
- Jurisdictions
- none stated
- Industry
- unknown
- Employees
- unknown
- Data
- confidential material: yes · legally privileged material: not stated · personal data: likely · sensitive personal data: not stated
- Local processing
- not required
- Cloud allowed
- unknown
- Users
- unknown
- Capability
- unknown
- Preferred setup
- you did not state one
- Data risk
- high
Read by fixed rules, no language model · 40% confident it read the question correctly
We could not place: organisation.industry, requirements.dataResidency, requirements.existingStack, budget, jurisdictions.primary, organisation.employees, data sensitivity, deploymentPreference, technicalCapability
Not accounted for
Nothing in this comparison depends on your industry, any residency requirement, the systems you already run, your budget, the jurisdiction you operate in, your headcount, how sensitive the material is, a hosting preference or the technical capability you have in-house — none of it was supplied. Where a figure would move for one of those, it is stated as an assumption rather than hidden inside the number.
02Comparison
| Dimension | Vertex AI TrainingToolCONSIDER IF…for enterprise SaaS under this brief | Azure AI SearchToolCONSIDER IF…for enterprise SaaS under this brief | Azure Machine LearningToolCONSIDER IF…for enterprise SaaS under this brief | Amazon SageMaker TrainingToolCONSIDER IF…for enterprise SaaS under this brief |
|---|---|---|---|---|
| Deployment modelRegistry entry: how this is delivered, and which solution class it is scored as. | Enterprise SaaS The registry records Vertex AI Training as available on vendor cloud or private cloud; it is scored here as enterprise SaaS. ASSESSMENT | Enterprise SaaS The registry records Azure AI Search as available on vendor cloud or private cloud; it is scored here as enterprise SaaS. ASSESSMENT | Enterprise SaaS The registry records Azure Machine Learning as available on vendor cloud or private cloud; it is scored here as enterprise SaaS. ASSESSMENT | Enterprise SaaS The registry records Amazon SageMaker Training as available on vendor cloud or private cloud; it is scored here as enterprise SaaS. ASSESSMENT |
| Verdict for this briefSolution-class analysis (buildOptions) over this brief. The verdict is on the class of answer, not on the product. | CONSIDER IF… For this brief — confidential documents — enterprise SaaS is conditional: worth it only if the conditions in the options section hold. Change the brief and this verdict changes. RECOMMENDATION | CONSIDER IF… For this brief — confidential documents — enterprise SaaS is conditional: worth it only if the conditions in the options section hold. Change the brief and this verdict changes. RECOMMENDATION | CONSIDER IF… For this brief — confidential documents — enterprise SaaS is conditional: worth it only if the conditions in the options section hold. Change the brief and this verdict changes. RECOMMENDATION | CONSIDER IF… For this brief — confidential documents — enterprise SaaS is conditional: worth it only if the conditions in the options section hold. Change the brief and this verdict changes. RECOMMENDATION |
| Functional fitOntology overlap between the objective in this brief and the use cases the registry records for the subject (matchRecipes). Recorded for tools; not recorded per model. | unknown Vertex AI Training is a platform for running a model you choose, not a product built for one job, so there is no use-case overlap to measure — what it does depends on what you build on it. The fit that can be assessed is the deployment's, in the rows below. ASSESSMENT | unknown Azure AI Search is a platform for running a model you choose, not a product built for one job, so there is no use-case overlap to measure — what it does depends on what you build on it. The fit that can be assessed is the deployment's, in the rows below. ASSESSMENT | unknown Azure Machine Learning is a platform for running a model you choose, not a product built for one job, so there is no use-case overlap to measure — what it does depends on what you build on it. The fit that can be assessed is the deployment's, in the rows below. ASSESSMENT | unknown Amazon SageMaker Training is a platform for running a model you choose, not a product built for one job, so there is no use-case overlap to measure — what it does depends on what you build on it. The fit that can be assessed is the deployment's, in the rows below. ASSESSMENT |
| Deployment fitHosting preference, data egress, headcount band and technical capability, weighted 0.30 / 0.35 / 0.15 / 0.20 (matchRecipes). | 74% You stated no hosting preference, so no option is favoured on that basis. No hard restriction on where processing happens was stated. This is a vendor-operated service. Your cloud account does not determine where it runs; confirm the vendor’s data processing and integration with your existing systems. ASSESSMENT | 74% You stated no hosting preference, so no option is favoured on that basis. No hard restriction on where processing happens was stated. This is a vendor-operated service. Your cloud account does not determine where it runs; confirm the vendor’s data processing and integration with your existing systems. ASSESSMENT | 74% You stated no hosting preference, so no option is favoured on that basis. No hard restriction on where processing happens was stated. This is a vendor-operated service. Your cloud account does not determine where it runs; confirm the vendor’s data processing and integration with your existing systems. ASSESSMENT | 74% You stated no hosting preference, so no option is favoured on that basis. No hard restriction on where processing happens was stated. This is a vendor-operated service. Your cloud account does not determine where it runs; confirm the vendor’s data processing and integration with your existing systems. ASSESSMENT |
| Data controlExternal transfer computed from the architecture graph of the deployment (computeExternalTransfer) — what actually crosses out of your network. | yes External data transfer: yes. No catalogue deployment names Vertex AI Training, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. Confidential content leaves your control on the Employees → Vendor assistant (web and desktop clients) link. ASSESSMENT | yes External data transfer: yes. No catalogue deployment names Azure AI Search, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. Confidential content leaves your control on the Employees → Vendor assistant (web and desktop clients) link. ASSESSMENT | yes External data transfer: yes. No catalogue deployment names Azure Machine Learning, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. Confidential content leaves your control on the Employees → Vendor assistant (web and desktop clients) link. ASSESSMENT | yes External data transfer: yes. No catalogue deployment names Amazon SageMaker Training, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. Confidential content leaves your control on the Employees → Vendor assistant (web and desktop clients) link. ASSESSMENT |
| Data residencyVendor documents we have fetched. A residency commitment we have not read is “unknown” — never assumed (CONTENT-RULES §5). | unknown We have fetched a supported-countries page for Vertex AI Training, which says where the product may be bought — not where content is processed or stored. No residency commitment has been read, so the residency question is unknown. The vendor is headquartered in United States, which is where a transfer question starts, not where it ends. ASSESSMENT | unknown We have fetched a supported-countries page for Azure AI Search, which says where the product may be bought — not where content is processed or stored. No residency commitment has been read, so the residency question is unknown. The vendor is headquartered in United States, which is where a transfer question starts, not where it ends. ASSESSMENT | unknown We have fetched a supported-countries page for Azure Machine Learning, which says where the product may be bought — not where content is processed or stored. No residency commitment has been read, so the residency question is unknown. The vendor is headquartered in United States, which is where a transfer question starts, not where it ends. ASSESSMENT | unknown We have fetched a supported-countries page for Amazon SageMaker Training, which says where the product may be bought — not where content is processed or stored. No residency commitment has been read, so the residency question is unknown. The vendor is headquartered in United States, which is where a transfer question starts, not where it ends. ASSESSMENT |
| Governance controlsThe four commitments a processor is asked for — DPA, subprocessor list, no training on your content, zero retention — counted against fetched vendor documents. | 2 of 4 Published and fetched: data processing agreement, subprocessor list. Still open: training on customer data, zero retention option — ask the vendor. FACT | 2 of 4 Published and fetched: data processing agreement, subprocessor list. Still open: training on customer data, zero retention option — ask the vendor. FACT | 2 of 4 Published and fetched: data processing agreement, subprocessor list. Still open: training on customer data, zero retention option — ask the vendor. FACT | 2 of 4 Published and fetched: data processing agreement, subprocessor list. Still open: training on customer data, zero retention option — ask the vendor. FACT |
| Integration effortThe FDE-day band the catalogue deployment was costed from (RECIPE_IMPLEMENTATION_DAYS). | 4–12 FDE-days 4–12 FDE-days to implement. No catalogue deployment names Vertex AI Training, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. ASSESSMENT | 4–12 FDE-days 4–12 FDE-days to implement. No catalogue deployment names Azure AI Search, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. ASSESSMENT | 4–12 FDE-days 4–12 FDE-days to implement. No catalogue deployment names Azure Machine Learning, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. ASSESSMENT | 4–12 FDE-days 4–12 FDE-days to implement. No catalogue deployment names Amazon SageMaker Training, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. ASSESSMENT |
| Maintenance burdenWho operates the result, read from the solution class and the difficulty factors the deployment carries. | vendor-operated The vendor runs the service. Your standing work is access control, the policy staff work under, and re-reading the contract and subprocessor list when they change — not patching or capacity. ASSESSMENT | vendor-operated The vendor runs the service. Your standing work is access control, the policy staff work under, and re-reading the contract and subprocessor list when they change — not patching or capacity. ASSESSMENT | vendor-operated The vendor runs the service. Your standing work is access control, the policy staff work under, and re-reading the contract and subprocessor list when they change — not patching or capacity. ASSESSMENT | vendor-operated The vendor runs the service. Your standing work is access control, the policy staff work under, and re-reading the contract and subprocessor list when they change — not patching or capacity. ASSESSMENT |
| Deployment difficultyDifficulty 1–5 for the deployment and for this team (scoreDifficulty): the same stack scores lower for an organisation with its own engineers. | 2/5 2/5. Starting point 1/5: a vendor product, configured rather than installed. +0.5 Single sign-on adds an identity provider, group-to-role mapping and a joiner/leaver process to the deployment. ASSESSMENT | 2/5 2/5. Starting point 1/5: a vendor product, configured rather than installed. +0.5 Single sign-on adds an identity provider, group-to-role mapping and a joiner/leaver process to the deployment. ASSESSMENT | 2/5 2/5. Starting point 1/5: a vendor product, configured rather than installed. +0.5 Single sign-on adds an identity provider, group-to-role mapping and a joiner/leaver process to the deployment. ASSESSMENT | 2/5 2/5. Starting point 1/5: a vendor product, configured rather than installed. +0.5 Single sign-on adds an identity provider, group-to-role mapping and a joiner/leaver process to the deployment. ASSESSMENT |
| Estimated costIndicative cost for this headcount (estimateCost), plus any per-token price we have actually fetched. A price we have not read is not printed. | USD 3,100 – 23,000 + licences USD 3,100 – 23,000 — one-off — for Vertex AI Training at this headcount. No catalogue deployment names Vertex AI Training, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. Licences are not in that figure: no per-seat price has been read from the vendor’s own pricing page, so the software line is excluded from the total rather than guessed. Read it as implementation only. ASSESSMENT | USD 3,100 – 23,000 + licences USD 3,100 – 23,000 — one-off — for Azure AI Search at this headcount. No catalogue deployment names Azure AI Search, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. Licences are not in that figure: no per-seat price has been read from the vendor’s own pricing page, so the software line is excluded from the total rather than guessed. Read it as implementation only. ASSESSMENT | USD 3,100 – 23,000 + licences USD 3,100 – 23,000 — one-off — for Azure Machine Learning at this headcount. No catalogue deployment names Azure Machine Learning, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. Licences are not in that figure: no per-seat price has been read from the vendor’s own pricing page, so the software line is excluded from the total rather than guessed. Read it as implementation only. ASSESSMENT | USD 3,100 – 23,000 + licences USD 3,100 – 23,000 — one-off — for Amazon SageMaker Training at this headcount. No catalogue deployment names Amazon SageMaker Training, so this is read from “Enterprise SaaS assistant with governance controls”, the best-matching enterprise SaaS deployment for this brief. Licences are not in that figure: no per-seat price has been read from the vendor’s own pricing page, so the software line is excluded from the total rather than guessed. Read it as implementation only. ASSESSMENT |
| CustomisationRegistry entry: whether the source is open and where the deployment can be changed. | vendor-configured Vertex AI Training is a vendor product: you configure what the vendor exposes — policies, connectors, retention settings — and nothing below that line. ASSESSMENT | vendor-configured Azure AI Search is a vendor product: you configure what the vendor exposes — policies, connectors, retention settings — and nothing below that line. ASSESSMENT | vendor-configured Azure Machine Learning is a vendor product: you configure what the vendor exposes — policies, connectors, retention settings — and nothing below that line. ASSESSMENT | vendor-configured Amazon SageMaker Training is a vendor product: you configure what the vendor exposes — policies, connectors, retention settings — and nothing below that line. ASSESSMENT |
| Relevant compliance evidenceThe compliance engine over this brief and this subject (assessCompliance), with each issue cited to the instrument it quotes where the page was fetched. | 8 issues · 0 cited 8 issues spotted for this brief, 0 of them legal requirements; 0 carry a quote from the instrument they rest on. Leading with: Confidentiality duties bind independently of data protection law. ASSESSMENT | 8 issues · 0 cited 8 issues spotted for this brief, 0 of them legal requirements; 0 carry a quote from the instrument they rest on. Leading with: Confidentiality duties bind independently of data protection law. ASSESSMENT | 8 issues · 0 cited 8 issues spotted for this brief, 0 of them legal requirements; 0 carry a quote from the instrument they rest on. Leading with: Confidentiality duties bind independently of data protection law. ASSESSMENT | 8 issues · 0 cited 8 issues spotted for this brief, 0 of them legal requirements; 0 carry a quote from the instrument they rest on. Leading with: Confidentiality duties bind independently of data protection law. ASSESSMENT |
Comparing
- Vertex AI Trainingremove Vertex AI Training from this comparison
- Azure AI Searchremove Azure AI Search from this comparison
- Azure Machine Learningremove Azure Machine Learning from this comparison
- Amazon SageMaker Trainingremove Amazon SageMaker Training from this comparison
Add one that serves the same objective
This table is full at 4 subjects. Remove one to add another — beyond four, the columns stop being readable and the comparison stops being one.
- Alibaba Cloud Model Studio
- Amazon Bedrock
- Amazon Bedrock AgentCore
- Amazon OpenSearch Serverless
- Amazon SageMaker AI
- Gemini Enterprise
- Google Vertex AI
- IBM watsonx.ai
03What this does not tell you
- WARNINGCompare no jurisdiction
No jurisdiction was supplied, so only the cross-cutting rules ran. A comparison for a regulated deployment should name one.
- MINORCompare objective derived
No objective was given, so functional fit is measured against choosing a cloud platform — the use case most of these subjects share. Add one to the link to measure a different job.
- MINORCompare recipe substituted
No catalogue deployment names Vertex AI Training, so its cost, effort and difficulty are read from “Enterprise SaaS assistant with governance controls”, the closest enterprise SaaS deployment for this brief.
- MINORCompare recipe substituted
No catalogue deployment names Azure AI Search, so its cost, effort and difficulty are read from “Enterprise SaaS assistant with governance controls”, the closest enterprise SaaS deployment for this brief.
- MINORCompare recipe substituted
No catalogue deployment names Azure Machine Learning, so its cost, effort and difficulty are read from “Enterprise SaaS assistant with governance controls”, the closest enterprise SaaS deployment for this brief.
- MINORCompare recipe substituted
No catalogue deployment names Amazon SageMaker Training, so its cost, effort and difficulty are read from “Enterprise SaaS assistant with governance controls”, the closest enterprise SaaS deployment for this brief.
Structured issue-spotting to support your own review — not legal advice. Verify against the cited primary sources and your counsel.
04Evidence
- 01Tier 2official vendor legal documentationVendor legal and technical documentation
Global Locations - Regions & Zones | Google Cloud
https://cloud.google.com/about/locations
AgeingRetrieved 20 Sep 2026sha256:54edd9a1f8661 record
- 02Tier 2official vendor legal documentationVendor legal and technical documentation
Region availability for Foundry Models sold by Azure - Microsoft Foundry
https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure-region-availability
AgeingRetrieved 20 Sep 2026sha256:006f84ba9ea61 record
- 03Tier 2official vendor legal documentationVendor legal and technical documentation
Global Infrastructure Regions & AZs
https://aws.amazon.com/about-aws/global-infrastructure/regions_az/
AgeingRetrieved 19 Sep 2026sha256:a5d63a92cf601 record
- 04Tier 2official vendor legal documentationVendor legal and technical documentation
Cloud Data Processing Addendum | Google Cloud
https://cloud.google.com/terms/data-processing-addendum
AgeingRetrieved 20 Sep 2026sha256:eedabd6f9ca11 record
- 05Tier 2official vendor legal documentationVendor legal and technical documentation
Google Cloud Platform Subprocessors | Google Cloud
https://cloud.google.com/terms/subprocessors
AgeingRetrieved 20 Sep 2026sha256:1549c29f3f771 record
- 06Tier 2official vendor legal documentationVendor legal and technical documentation
https://www.microsoft.com/licensing/docs/view/Microsoft-Products-and-Services-Data-Protection-Addendum-DPA
AgeingRetrieved 20 Sep 2026sha256:7bcef261059f1 record
- 07Tier 2official vendor legal documentationVendor legal and technical documentation
Microsoft Data Access | Microsoft Trust Center
https://www.microsoft.com/en-us/trust-center/privacy/data-access
AgeingRetrieved 20 Sep 2026sha256:a771da2496e71 record
- 08Tier 2official vendor legal documentationVendor legal and technical documentation
GDPR - Amazon Web Services (AWS)
https://aws.amazon.com/compliance/gdpr-center/
AgeingRetrieved 19 Sep 2026sha256:5fd5e4b750981 record
- 09Tier 2official vendor legal documentationVendor legal and technical documentation
Amazon Web Services (AWS) Sub-processors
https://aws.amazon.com/compliance/sub-processors/
AgeingRetrieved 19 Sep 2026sha256:82d65e6186481 record