AI and Azure Machine Learning

Smooth the way to digital transformation with Artificial Intelligence, regardless of your company's experience. Whether you need to streamline a specific process or you want to revolutionise the industry, you can achieve it with accessible and useful AI resources throughout your company. Dynamics 365 AI gives teams the freedom to troubleshoot and make decisions for themselves with the help of smart tools.

Tailor the transformation to your needs
Simplify AI adoption with intuitive interfaces, detailed guidelines, and apps that integrate seamlessly for a streamlined experience.

Remove business silos
Gain a deeper understanding of your customers and organisation by unifying relationships, processes, and data across apps.

Get in-depth insights
Make each touchpoint more relevant and responsive with proactive, data-driven insights into customer needs and behaviours.

Adapt your resources to company needs
Adapt to market conditions and changing customer needs with easily adjustable AI functionality.

Accelerate the end-to-end machine learning lifecycle

Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps-DevOps for machine learning.

Innovate on a secure, trusted platform designed for responsible ML.

Boost productivity and access machine learning for all users

Rapidly build and deploy machine learning models using tools that meet your needs regardless of skill level. Use the no-code designer to get started or built-in collaborative Jupyter notebooks for a code-first experience. Accelerate model creation with automated machine learning and access built-in feature engineering, algorithm selection, and hyperparameter sweeping to develop highly accurate models.

Operationalise at scale with MLOps

MLOps, or DevOps for Machine Learning, streamlines the machine learning lifecycle from building models to deployment and management. Use ML pipelines to build repeatable workflows and a rich model registry to track your assets. Manage production workflows at scale using advanced alerts and machine learning automation capabilities. Profile, validate, and deploy machine learning models anywhere from the cloud to the edge to manage production ML workflows at scale in an enterprise-ready fashion.

Build responsible machine learning solutions

Access state-of-the-art technology to guarantee fairness and transparency in machine learning models.

Use model interpretability to get explanations about predictions and better understand the behaviour of models. Reduce bias in models by applying common fairness metrics, performing automatic comparisons, and using recommended mitigations.

Innovate on an open and flexible platform

Get built-in support for open-source tools and frameworks for machine learning model training and inferencing. Use familiar frameworks like PyTorch, TensorFlow, and scikit-learn, or the open and interoperable ONNX format. Choose the development tools that best meet your needs, including popular IDEs, Jupyter notebooks and CLI, or languages such as Python and R. Use ONNX Runtime to optimise and accelerate inferencing across cloud and edge devices.

Advanced security, governance, and control

• Design machine learningmodels with the enterprise-grade virtual network functionality, security, and compliance of Azure.
• Protect your resources with built-in controls for identity, data, and network access, including custom roles.
• Restrict access to your corporate network or apply security policies from Azure.

Manage governance with policies, audit trails, quota and cost management, as well as a full legal compliance portfolio.