Exploring the Microsoft Azure AI Portfolio: A Framework for Azure AI Design Projects

By: Mark Petroff | October 15, 2024

In today’s rapidly evolving technological landscape, leveraging artificial intelligence (AI) is crucial for businesses aiming to stay competitive. Microsoft Azure offers a comprehensive AI portfolio designed to help organizations integrate AI seamlessly into their operations.  Yet the Microsoft Portfolio, when viewed in its’ entirety, can seem overwhelming to users.

And given the early stage of Generative AI capabilities in the industry, many Azure AI projects are still limited in scope, not taking advantage of the full range of Azure AI and Azure Open AI capabilities.

Yet while the world is excited about the introduction of Azure Open AI Services, that’s not all the Azure AI Portfolio has to offer.  Azure AI and ML services have been around for quite some time, and Core BTS has been there to leverage them in our client projects.

An Azure AI Design from Core BTS reflects the deep knowledge, extensive experience, and proven success in planning and deploying AI and Machine Learning solutions on Microsoft Azure. This includes empowering customers to deploy AI cognitive services and machine learning solutions from the assessment phase to design, pilot, implementation, and post-implementation phases

This blog post will provide an overview of how Core BTS uses the Azure AI portfolio framework to develop an Azure AI Design project for our clients.

The Microsoft Azure AI and Azure Open AI Portfolio

The Microsoft Azure AI and Azure Open AI portfolios encompass a wide range of services and tools that cater to various AI needs, from machine learning to cognitive services.

With all the recent attention AI has garnered in the news, it’s easy to forget that AI itself is not a new concept. Azure has incorporated AI and Machine Learning into Azure for some time. However, the late 2022 release of Chat GPT from Open AI capture public imagination and thrust AI into the zeitgeist.

Azure AI Services

Azure AI services offer a comprehensive suite of pre-built models, APIs, and SDKs that enable developers to integrate advanced AI capabilities into applications, including vision, speech, language, and decision-making, enhancing functionality and user experience.

Azure AI services include:

  • Azure AI Vision
    Azure AI Vision is a unified service that offers innovative computer vision capabilities. It allows applications to analyze images, read text, and detect faces using prebuilt image tagging, optical character recognition (OCR), and facial recognition. This service enhances visual recognition and understanding without requiring machine learning expertise
  • Azure AI Speech
    Azure AI Speech is a managed service offering industry-leading speech capabilities such as speech-to-text, text-to-speech, speech translation, and speaker recognition. It enables developers to build voice-enabled applications with high accuracy, natural-sounding voices, and real-time translation, enhancing user experiences and accessibility

Why choose Core BTS as your Azure AI Design Partner?

Core BTS is the ideal Azure AI Design consultant due to our deep knowledge, extensive experience, and proven success in deploying AI and Machine Learning solutions on Microsoft Azure.

Unlike the man consultants that jumped onto the AI bandwagon of late, we’ve been designing projects incorporating Azure’s AI and ML capabilities for years.

We guide our clients from assessment to post-implementation, ensuring full leverage of Azure AI and OpenAI capabilities, thus maximizing investment value.

As a top-tier Microsoft partner, Core BTS has access to Microsoft’s resources to further enables effective development, marketing, and selling of AI solutions

Click here to speak with a Core BTS representative about your Azure AI Design project

  • Azure AI Language
    Azure AI Language is a cloud-based service that provides Natural Language Processing (NLP) features for understanding and analyzing text. It includes capabilities like sentiment analysis, language detection, key phrase extraction, and entity recognition. This service helps build intelligent applications using Language Studio, REST APIs, and client libraries

  • Azure AI Translator
    Azure AI Translator is a cloud-based service that uses AI to translate text and documents between languages in near real-time. It supports over 100 languages and dialects, offering customizable translation models for industry-specific terminology. This service enhances multilingual communication and integrates seamlessly with various applications

As you can see, Azure AI Services provide quite a range of capabilities, useful in building custom applications, designing services to improve user experience, and streamlining business applications.  Capabilities that not too long ago would have required a significant investment in time and resources are now available for uses limited only by the imagination.

Azure Open AI Services

Azure OpenAI Service offers access to OpenAI’s powerful language models, enabling advanced natural language processing tasks. It provides access to OpenAI’s cutting-edge models, including GPT-4, Codex, and DALL-E, directly within the Azure platform.

These models are co-developed with OpenAI and offer the same capabilities as OpenAI’s models but with the added security and enterprise features of the Azure platform

This service allows developers to create intelligent applications that can understand and generate human-like text, code, and images. With Azure’s robust infrastructure, developers can scale their AI solutions efficiently and securely.

Also included as part of the Azure Open AI Services portfolio are Azure AI Search, Azure AI Document Intelligence, and Azure AI Content Safety:

  • Azure AI Search
    Azure AI Search is a powerful search-as-a-service solution that enables developers to build sophisticated search experiences into their applications. It leverages AI capabilities to provide relevant and personalized search results, enhancing user experience.With features like natural language processing, cognitive search, and semantic search, Azure AI Search can understand user intent and context. It also integrates seamlessly with other Azure services, ensuring scalability, security, and compliance for enterprise-grade search solutions.
  • Azure AI Document Intelligence
    Azure AI Document Intelligence is a comprehensive solution that leverages advanced AI capabilities to extract, analyze, and understand information from various document types. It uses machine learning models to automate data extraction, classification, and processing, making it easier to manage large volumes of documents. This service enhances productivity by reducing manual effort and improving accuracy. It integrates seamlessly with other Azure services, providing a scalable and secure platform for document management and analysis.
  • Azure Content Safety
    Azure Content Safety ensures that AI applications adhere to ethical guidelines and mitigate harmful use, leveraging advanced AI models to identify and filter out offensive, inappropriate, or harmful content, ensuring a safer online environment.Content Safety can be integrated into applications to monitor user-generated content in real-time, providing a secure and compliant platform. Azure Content Safety enhances user trust and protects brand reputation by maintaining a positive and safe digital presence.

Azure Machine Learning

Azure Machine Learning is an enterprise-grade AI service for the end-to-end machine learning lifecycle. It offers powerful AI infrastructure, automated machine learning, responsible AI, and MLOps capabilities, enabling developers to build, train, deploy, and manage machine learning models efficiently and securely

In short, Azure Machine Learning provides you with advanced tools for designing and fine-tuning specialized AI models, and includes the following elements:

  • Machine Learning Studio
    Azure Machine Learning Studio is a web-based integrated development environment for constructing and operationalizing machine learning workflows on Azure. It enables data scientists to complete the end-to-end machine learning lifecycle, from data preparation to model deployment, using cloud-scalable compute in a single enterprise-ready tool
  • Model Catalog
    The Azure Model Catalog in Azure AI Studio is a hub for discovering, evaluating, customizing, and deploying AI models. It features a wide range of models from providers like OpenAI, Meta, and Hugging Face, enabling seamless integration into applications for various AI tasks
  • Project Flow
    Azure Project Flow is a cloud-based environment for training, deploying, and managing machine learning models. It provides a streamlined process for developing AI solutions, from data preparation to model deployment, ensuring scalability, security, and efficiency throughout the machine learning lifecycle

Azure AI Scenarios

By now you hopefully see the breadth of capabilities already built into the Azure AI portfolio. Far from being just another AI product, the Azure IA portfolio provides a range of elemental building blocks for next generation applications and services throughout your organization.

  • Responsible AI
    A sample use case for Responsible AI would be the development of a Conversational AI while incorporating ensuring ethical AI practices, such as bias detection, transparency, and accountability mechanisms to ensure that AI models are fair, explainable, and secure.
  • MLOps
    An example use case for MLOps is the deployment of machine learning models in a production environment to automate predictive maintenance in manufacturing. This involves using MLOps principles to manage the entire lifecycle of the models, from development to deployment and monitoring, ensuring they perform reliably and efficiently
  • LLMops
    A good LLMops use case could be the implementation of a large language model (LLM) for customer service chatbots. This involves operationalizing the LLM to handle customer inquiries, fine-tuning it for specific business needs, and continuously monitoring its performance to ensure it provides accurate and relevant response
  • Custom Copilots
    Custom Copilots can be used to enhance customer experiences, streamline internal functions, or build innovative solutions. For example, you can create a copilot for your public eCommerce website that can help customers check in-stock items, provide a price quote, or book a demo.

    Custom Copilots can be tailored to specific roles and functions, such as creating a guided copilot to provide online technical support, an online concierge to help customers choose the right product, or an order-desk assistant to help address inquires as to the status of a shipment. These copilots can be integrated into various channels, including internal websites, mobile apps, and even social media.
  • Prompt Engineering
    Prompt Engineering is a crucial aspect of the Azure AI portfolio. It involves designing and optimizing prompts to effectively interact with AI models, ensuring that the models generate accurate and relevant responses.

Putting it All Together:
Don’t Go It Alone. Core BTS can Play an Important Role in your AI Project

The Microsoft Azure AI portfolio offers a robust framework for developing AI-driven solutions tailored to your customers’ needs. By leveraging these tools, you can create innovative and efficient Azure Design projects that drive business success.

Yet, taking into account all that the Azure AI portfolio has to offer as part of your application design might be beyond the capabilities of your organization.

That’s why looking to a top-tier Microsoft Partner like Core BTS to develop your Azure AI Design project is highly beneficial. We possess deep knowledge, extensive experience, and proven success in planning and deploying AI and Machine Learning solutions on Microsoft Azure. We empower customers beginning with the assessment phase to design, pilot, implementation, and post-implementation phases. This ensures that your project leverages the full range of Azure AI and Azure OpenAI capabilities, maximizing the value of your investment.

In addition, Core BTS has access to Microsoft’s extensive resources, including AI expertise and a global network, which helps us develop, market, and sell AI solutions effectively. These partners can assist in building next-gen AI-powered applications, ensuring responsible and secure AI implementation, and contributing to the overall success of your AI transformation

Ready to start your Azure AI journey? Explore the full range of Azure AI services and see how they can transform your business today.

As Core's Managing Director of Modern Applications & Cloud Foundations, Mark leads the strategic vision, execution, and management of our modern applications professional services practice.

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