Unlocking business optimization with Azure OpenAI: three practical use cases explored

Discover the transformative potential of incorporating large language models into your business

We recently held a webinar: 3 ways to optimize your business with Azure Open AI. In this blog post, we delve into the insightful discussions from the webinar and explore the practical use cases presented by SoftwareOne’s experts - Katrin Strasser, Head of Language Technologies EMEA, Prithy Yathavamurthy, Head of Language Technologies APAC, and Robert Injac, Solution Architect.

With the increasing prominence of Large Language Models (LLMs), businesses are discovering new avenues for optimization and growth. Let's dive into the details and uncover the transformative potential of these technologies.

Introduction to SoftwareOne: driving innovation with AI and data

We are a world-leading and award-winning Applied AI and Data (Science and Engineering) services and consulting company that has been at the forefront of delivering modern AI projects in speech and language technologies, computer vision, decision intelligence and data platform, and MLOps for clients across various industries in all countries where SoftwareOne is present.

With many years of experience and expertise in software, cloud, AI, and big data, SoftwareOne has become one of the top global strategic partners for Microsoft Azure Open AI and has a close collaboration with the Microsoft Product Group, Engineering and specialized AI and Data Science teams. To date, we have delivered more than 25 LLM projects on Azure.

Our responsible AI framework, as well as working closely with governments and regulators, ensures the ethical and efficient use of AI technologies. And, our comprehensive capabilities, combined with Microsoft's recognition as a top AI and machine learning partner, make us a trusted resource for businesses seeking to optimize their operations.

The rise of Large Language Models: hype or innovation?

Large Language Models have gained significant attention in recent years, promising to revolutionize various industries. While LLMs may seem like a new phenomenon, the underlying technology of Natural Language Processing (NLP) has been in development for decades. However, the recent advancements in LLMs, such as Azure Open AI, have taken NLP to new heights of maturity and applicability. These models offer practical solutions for businesses in optimizing processes, empowering employees, engaging customers, and transforming products and services. LLMs are here to stay, providing immense potential in myriad ways for every company.

The business value of Azure Open AI

There is immense value and potential to be tapped by businesses with Azure Open AI. By leveraging LLMs, organizations can optimize their operations, gain valuable insights, and enhance their products and services. SoftwareOne's expertise lies in identifying the most suitable LLMs for specific use cases, considering factors like data requirements and operational costs. It is important to stress that the data used by Azure Open AI remains within the organization's systems, ensuring data privacy and security.

What are the most time-consuming or challenging processes that your business could benefit the most from Generative AI and content generation? Here are some practical use cases you may like to consider.

Practical use case #1: Automated content generation and large-scale media analysis

The first practical use case presented focuses on automated content generation and media analysis. SoftwareOne collaborated with a media company to develop a solution that automatically generates summaries and extracts metadata from video and audio clips. The solution enables program producers and editorial teams to easily search for relevant information, such as location, actors, or specific scenes. By leveraging LLMs and knowledge mining techniques, the media company can create a rich internal knowledge graph, empowering content creators and enhancing the efficiency of their media catalog.

Practical use case #2: the GPT-powered contact center

The second use case explores the transformation of customer support centers into intelligent and cost-saving centers. SoftwareOne has worked with various contact centers to address the challenge of unstructured data in customer interactions. By transcribing audio recordings and utilizing LLMs, SoftwareOne enabled analysts, operations teams, and management to search, summarize, and visualize the information within the recordings. This empowered the contact centers to extract valuable insights, optimize their operations, and provide better support to customers, turning the contact center into an invaluable source of business intelligence.

Practical use case #3: Ask Your Data/ enterprise fact-based question answering

The third use case focuses on the challenge of information retrieval within organizations. With data scattered across multiple sources, employees often struggle to find relevant information efficiently. SoftwareOne's solution leverages AI technologies to enable employees to search through various data sources using natural language queries. By combining cognitive search and LLMs, the solution extracts answers and provides structured information, allowing employees to quickly locate the information they need. This use case empowers organizations to become data-driven, increasing productivity and improving decision-making processes. To make it applicable to your organization, you need to ask yourself: “Which data from across the business would you like to have at your fingertips?"