| Service/Category | Description | Use Cases | Architectural Patterns |
| Azure Machine Learning | An enterprise-grade service for the end-to-end machine learning lifecycle, from data preparation and model training to deployment and MLOps. | Predictive maintenance, customer churn prevention, demand forecasting, medical image analysis, personalized recommendations. | MLOps: Automating and standardizing the machine learning lifecycle using CI/CD pipelines.
Batch Scoring: Processing large datasets to generate predictions offline. Real-Time Scoring: Deploying models as endpoints for low-latency, real-time predictions. |
| Azure AI ServicesA suite of pre-built, cloud-based APIs that enable developers to add cognitive capabilities to applications without deep machine learning expertise. | |||
| – Vision | APIs for image analysis, facial recognition, object detection, and optical character recognition (OCR). | Facial recognition for security, analysing product images for quality control, extracting text from documents. | Computer Vision Pipelines: Chaining together different vision services to process and extract insights from images or videos. |
| – Speech | Services for converting text to speech, speech to text, and real-time translation. | Voice-enabled applications, customer service chatbots, transcribing meeting notes, and multilingual voice assistants. | Event-Driven Architectures: Using services like Azure Event Grid to trigger speech-to-text processing when audio files are uploaded. |
| – Language | APIs for natural language understanding (NLU), sentiment analysis, key phrase extraction, and language translation. | Sentiment analysis of customer feedback, building chatbots and virtual assistants, creating content summarization tools. | Conversational AI: Integrating Language and Bot Service to create an interactive, natural-language experience. Semantic Search: Augmenting traditional search with NLU to provide more relevant results. |
| – Decision | APIs that help in making informed decisions by detecting anomalies, moderating content, and personalizing experiences. | Fraud detection in financial transactions, content moderation for social platforms, personalized product recommendations in e-commerce. | Personalization Engines: Using services like Azure AI Personalizer to continuously learn and optimize content for individual users. |
| – Azure OpenAI Service | Provides access to powerful large language models (LLMs) from OpenAI, such as GPT-4, for a variety of generative AI tasks. | Content generation, code completion, building intelligent chatbots, and summarizing large documents. | Retrieval-Augmented Generation (RAG): Combining an LLM with an external knowledge base (like Azure AI Search) to generate more informed and accurate responses. |
| Azure AI Search | A managed cloud search service that uses AI to provide intelligent search capabilities. | E-commerce product search, enterprise knowledge base search, and creating semantic search experiences for websites. | Hybrid Search: Combining vector search (for semantic similarity) and keyword search to deliver highly relevant results. |
| Azure Databricks | A fast, easy, and collaborative Apache Spark-based analytics platform for data engineering, data science, and machine learning. | Large-scale data processing and transformation, building ETL pipelines for ML models, and collaborative data science notebooks. | Lakehouse Architecture: Using Databricks to manage and process data in a data lake, enabling both data warehousing and machine learning workloads on a single platform. |
| Microsoft CoPilot | A family of generative AI assistants that work across Microsoft products (e.g., Office 365, GitHub, Dynamics 365) to assist users with a wide range of tasks. It is built on Azure’s foundational AI services. | Drafting documents and emails, summarizing meetings, generating code, analysing data in Excel, and creating presentations. | Copilot Studio: A low-code tool that allows businesses to create custom copilots by integrating with their own data and business processes. Integration with Azure AI: CoPilot leverages services like Azure OpenAI, Azure AI Search, and Language to provide its core functionality. |
