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Azure ML & Cloud
Azure Machine Learning
Enterprise MLOps platform — training, registry, endpoints
What it is
Microsoft's full-stack ML platform. Managed compute, AutoML, model registry, real-time and batch endpoints, designer GUI, MLflow integration — all inside your Azure tenancy.
How Vaaani uses it
- Training on managed GPU clusters with auto-scaling
- Hosting real-time endpoints with built-in monitoring
- AutoML for non-data-scientists on the customer team
- Compliance-friendly deployment for BFSI / health customers
Why it makes the cut
When the customer is on Microsoft 365 and has an enterprise Azure agreement, AzureML is the path of least friction — IT-approved, billed in one place, audit-ready.
Sample code
from azure.ai.ml import MLClient from azure.identity import DefaultAzureCredential ml = MLClient(DefaultAzureCredential(), subscription_id="...", workspace_name="vaaani-prod") ml.jobs.create_or_update(training_job)
Related in the Vaaani stack
Have a project that needs Azure?
30-min discovery call. You describe the busywork; I map it to an AI worker and a budget.