Azure Machine Learning Consulting Services

Unlock the power of AI and predictive analytics with Azure Machine Learning.

AGER BI helps organisations build, train, and deploy ML models using Azure’s scalable cloud platform to deliver business-ready insights and automation.

Organisations we’ve helped

What we’ve helped our clients achieve

0M

In savings and new value unlocked

0+

Data projects delivered with lasting business impact

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Years of solving complex data challenges

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Users supported across Australia and New Zealand

Azure ML Consulting Services That Predicts Outcomes

AI Strategy & Roadmap

Define your AI vision and identify high-impact opportunities to apply ML across your organisation.

Model Development & Training

Build, train, and tune custom ML models using Python, R, or AutoML in Azure ML Studio.

Data Preparation & Feature Engineering

Prepare structured and unstructured data pipelines for training using Azure Data Factory and Synapse integration.

MLOps & Deployment Pipelines

Implement CI/CD pipelines for model versioning, deployment, and monitoring across environments.

Model Monitoring & Optimisation

Track drift, retrain models, and automate version control using Azure ML’s integrated monitoring features.

Integration With Power BI & Synapse

Operationalise ML outputs into Power BI dashboards and Synapse analytics pipelines for real-time insights.

What BI Platform Is Right for Your Business?

Get a tailored recommendation in under 60 seconds

What Azure ML Enables

Predictive Analytics and Forecasting

Anticipate demand, revenue, or resource utilisation with predictive models that learn from historical data and surface trends before they occur.

Anomaly Detection and Quality Control

Detect outliers in financial transactions, sensor readings, or operational metrics in real time to prevent issues before they escalate.

Automated Machine Learning (AutoML)

Accelerate AI development with AutoML, which automatically selects, trains, and tunes algorithms, reducing time-to-value for business users.

End-to-End MLOps Pipelines

Deploy, monitor, and retrain models using CI/CD and version control. Ensure model reproducibility and governance throughout the ML lifecycle.

Integration with Synapse, Data Factory & Power BI

Connect Azure ML outputs directly to existing analytics platforms for real-time dashboards and embedded predictive insights.

Support for Popular Frameworks and Languages

Work natively with Python, R, TensorFlow, and PyTorch, allowing data scientists to use familiar tools while leveraging Azure’s scalability.

Scalable Cloud Compute and GPU Training

Train large-scale or deep-learning models faster using distributed GPU clusters and elastic compute that scales automatically.

Source Secure & Compliant AI Environment

Protect data and models with enterprise-grade encryption, RBAC, private networking, and compliance with ISO 27001 and HIPAA standards.

Operationalised AI Across Business Functions

Embed predictive scoring, automation, and intelligent decision-making into everyday workflows, turning insights into action across departments.

How We Deliver

And here’s how we deliver Azure ML models for your organisation

1: Discover / Access

Identify AI opportunities and assess data readiness.

2: Design / Prototype

Develop proof-of-concept models aligned to business goals.

3: Build / Train

Create, test, and validate ML models using Azure ML Studio and pipelines.

4: Deploy / Operationalise

Integrate models into your applications, dashboards, or data workflows.

5: Monitor / Evolve

Continuously track model accuracy, retrain, and adapt as new data becomes available.

Predictive Insights

Automation & Efficiency

Real-Time Decisioning

Model Governance

Data Integration

Scalable Cloud Training

Secure MLOps Deployment

Continuous Improvement

Speak with an expert
How we deliver results

Your trusted certified Microsoft experts

Microsoft Azure Data Engineer Associate logo

Microsoft Azure Data Engineer Associate

Microsoft Power BI Data Analyst Associate logo

Microsoft Power BI Data Analyst Associate

fabric analytics engineer logo

Fabric Analytics Engineer Associate

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Databricks Associate Developer for Apache Spark 3.0

We are certified specialists in Microsoft platforms such as Power BI, Fabric, Azure Data Factory, Azure SQL Database, Azure Synapse Analytics and Azure Databricks. We are also experts in Qlik View, Qlik Sense, Snowflake and Tableau.

What Azure ML Can Do For Your Business

Number 1

Accelerate AI Adoption

  • Transform AI from an abstract concept into a practical business capability. Azure Machine Learning enables you to move quickly from experimentation to production with built-in tools like AutoML, pre-trained models, and drag-and-drop interfaces. This helps your teams start delivering measurable value from AI initiatives without needing a large data science department.

Number 2

Reduce Development Complexity

  • Eliminate the heavy lifting of infrastructure setup, dependency management, and scaling. Azure ML provides an end-to-end, cloud-managed environment where data scientists and developers can collaborate, version control models, and run experiments efficiently, freeing your team to focus on insights rather than configuration.

Number 3

Operationalise Predictive Insights

  • Take machine learning out of the lab and embed it directly into your operations. Azure ML seamlessly connects with Synapse, Power BI, and Data Factory to deliver predictive insights within dashboards, reports, and workflows, enabling faster, more confident business decisions.
Number 4

Enable Scalable, Reproducible Experiments

  • Build repeatable, auditable, and consistent machine learning pipelines. Azure ML’s MLOps framework standardises how models are trained, tested, deployed, and retrained, ensuring reliability, governance, and traceability across your AI lifecycle.

Number 5

Drive ROI Through Automation

  • Use predictive models to automate manual processes, from demand forecasting to anomaly detection. By operationalising AI with Azure ML, you can reduce human error, improve response times, and unlock new efficiencies that deliver measurable return on investment.

Number 6

Ensure Security & Compliance

  • Protect your organisation’s data and intellectual property with Azure’s enterprise-grade security framework. Azure ML supports encryption at rest and in transit, role-based access control, and compliance with major global standards such as ISO 27001, HIPAA, and the Australian Privacy Principles, ensuring that innovation never compromises safety.

How Azure ML Is Used Across Teams and Industries

Finance

Automate fraud detection, credit scoring, and risk modelling using Azure ML integrated with Synapse data.

Mining & Resources

Use ML for equipment failure prediction, energy optimisation, and safety monitoring.

Healthcare

Predict patient outcomes and optimise resource allocation using ML models trained on clinical and operational data.

Education & Government

Apply ML to policy analysis, resource planning, and student performance prediction.

Manufacturing

Detect anomalies in production and predict quality deviations with real-time ML scoring.

Retail

Build recommendation engines, optimise pricing strategies, and forecast demand using AutoML.

FAQ

Azure ML is Microsoft’s cloud platform for building, training, and deploying AI and ML models.

It connects seamlessly with Synapse, Data Factory, and Power BI to operationalise end-to-end data science workflows.

Yes. Azure ML Studio provides a drag-and-drop interface for building models using AutoML.

MLOps automates model deployment, version control, and monitoring to streamline production AI management.

We handle everything from AI strategy and data preparation to model deployment, ensuring business outcomes, not just models.

Unlock the full potential of your data

Let’s talk about how we can help you get better visibility, better reporting, and better results from your data.

1300 381 500

info@agerbi.com.au