Azure AI Services

Build, Train, and Deploy Custom ML Models at Scale

ML Strategy & Consulting

Data Preparation & Feature Engineering

Define clear ML strategies, identify high-impact use cases, and assess your organizational readiness for advanced machine learning adoption.

Data Preparation & Feature Engineering

Expertise in cleaning, transforming, and preparing complex datasets for optimal model training, including advanced feature engineering.

Model Development & Training

Data Preparation & Feature Engineering

Automated Machine Learning (AutoML)

Build and train custom machine learning models using a wide range of algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn), leveraging Azure's scalable compute.

Automated Machine Learning (AutoML)

Accelerate model development by automating model selection, hyperparameter tuning, and data preprocessing for faster results.

MLOps (Machine Learning Operations)

Automated Machine Learning (AutoML)

MLOps (Machine Learning Operations)

Implement robust MLOps practices for continuous integration, continuous delivery (CI/CD) of ML models, model monitoring, versioning, and lifecycle management.

Model Deployment & Integration

Automated Machine Learning (AutoML)

MLOps (Machine Learning Operations)

Deploy trained models as scalable web services or in edge environments, ensuring seamless integration with your existing applications and business processes.

Responsible AI Practices

Integrate responsible AI principles, including fairness, interpretability, and privacy, throughout the ML lifecycle.

Retail: Demand Forecasting & Inventory Optimization

Challenge: A large retail chain struggled with accurate demand forecasting, leading to frequent stockouts or overstocking, impacting sales and carrying costs.

Solution: Built a custom ML model on Azure Machine Learning that analyzed historical sales data, promotional events, weather patterns, and economic indicators to predict demand for thousands of SKUs with high accuracy.

Impact: Reduced inventory holding costs by 15%, minimized stockouts, and improved sales revenue through optimized product availability.

Financial Services: Customer Lifetime Value (CLV) Prediction

Challenge: A bank wanted to identify high-value customers and tailor engagement strategies, but lacked a reliable method to predict individual customer lifetime value.

Solution: Developed an ML model on Azure Machine Learning that predicted CLV by analyzing customer transaction history, product engagement, and demographic data. The model’s insights were integrated into their CRM system for targeted marketing.

Impact: Enhanced customer segmentation, improved the effectiveness of marketing campaigns, and increased overall customer profitability.

CloudGuidant

Azure AI Services by Cloud Guidant

Build, Train, and Deploy Custom ML Models at Scale

ML Strategy & Consulting

Data Preparation & Feature Engineering

Data Preparation & Feature Engineering

Data Preparation & Feature Engineering

Data Preparation & Feature Engineering

Data Preparation & Feature Engineering

Model Development & Training

Data Preparation & Feature Engineering

Automated Machine Learning (AutoML)

Automated Machine Learning (AutoML)

Automated Machine Learning (AutoML)

Automated Machine Learning (AutoML)

MLOps (Machine Learning Operations)

Automated Machine Learning (AutoML)

MLOps (Machine Learning Operations)

Model Deployment & Integration

Automated Machine Learning (AutoML)

MLOps (Machine Learning Operations)

Responsible AI Practices

Responsible AI Practices

Responsible AI Practices

Projects & Industry Impact

Retail: Demand Forecasting & Inventory Optimization

Financial Services: Customer Lifetime Value (CLV) Prediction

Partner with Cloud Guidant

Azure AI Services by Cloud Guidant

Build, Train, and Deploy Custom ML Models at Scale

ML Strategy & Consulting

Data Preparation & Feature Engineering

Data Preparation & Feature Engineering

Data Preparation & Feature Engineering

Data Preparation & Feature Engineering

Data Preparation & Feature Engineering

Model Development & Training

Data Preparation & Feature Engineering

Automated Machine Learning (AutoML)

Automated Machine Learning (AutoML)

Automated Machine Learning (AutoML)

Automated Machine Learning (AutoML)

MLOps (Machine Learning Operations)

Automated Machine Learning (AutoML)

MLOps (Machine Learning Operations)

Model Deployment & Integration

Automated Machine Learning (AutoML)

MLOps (Machine Learning Operations)

Responsible AI Practices

Responsible AI Practices

Responsible AI Practices

Projects & Industry Impact

Retail: Demand Forecasting & Inventory Optimization

Financial Services: Customer Lifetime Value (CLV) Prediction

Partner with Cloud Guidant

This website uses cookies.