Embarking on an Azure AI/ML journey can appear challenging for certain organizations and engineers, often leading to roadblocks in their initial scenarios. To address this challenge, providing a user-friendly and intuitive template becomes crucial. Such a template should serve as a guiding example, illustrating the complete AI/ML/LLM lifecycle, showcasing the integration of MLOps practices, detailing the setup of training pipelines, offering insights into the processes of model training, deployment, access control, and integration with other services. This ensures a smoother and more comprehensible transition into the world of Azure AI and ML.

AI-in-a-Box aims to provide an "Azure AI/ML Easy Button" for common scenarios within Azure ML, Edge AI, Cog Services and Azure OpenAI. Something that shows you how the pieces fit together in easy to deploy templates. Using the patterns available here, engineers will be able to quickly setup an Azure ML/AI Edge/Cog Services and/or Azure Open AI environment which optionally includes data ingestion, model training and creation, scaling patterns and edge deployments. So, if you’re seeking to shed some light into the realm of Azure ML/AI and Open AI, you’ve come to the right spot.