aganiezgoda / AI-in-a-Box

AI-in-a-Box

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.

Available Patterns

Pattern	Description	Category	Supported Use Cases and Features
Azure ML Operationalization in-a-box	Boilerplate Data Science project from model development to deployment and monitoring	ML-in-a-Box	End-to-end MLOps project template Outer Loop (infrastructure setup) Inner Loop (model creation and deployment lifecycle)
Cognitive Services Landing Zone in-a-box	Minimal enterprise-ready networking and AI Services setup to support most Cognitive Services scenarios in a secure environment	AOAI-in-a-Box	Hub-and-Spoke Vnet setup and peering Cognitive Service deployment Private Endpoint setup Private DNS integration with PaaS DNS resolver
Doc Intelligence in-a-box	This accelerator enables companies to automate PDF form processing, modernize operations, save time, and cut costs as part of their digital transformation journey.	AI Services-in-a-Box	Receive PDF Forms Function App and Logic App for Orchestration Document Intelligence Model creation for form processing and content extraction Saves PDF data in Azure Cosmos DB
Semantic Kernel Bot in-a-box	Extendable solution accelerator for advanced Azure OpenAI Bots	AOAI-in-a-Box	Deploy Azure OpenAI bot to multiple channels (Web, Teams, Slack, etc) Built-in Retrieval-Augmented Generation (RAG) support Implement custom AI Plugins

Key contacts

Contact	GitHub ID	Email
Alex Morales	@msalemor	[e-mail]
Andrés Padilla	@AndresPad	[e-mail]
Chris Ayers	@codebytes	[e-mail]
Eduardo Noriega	@EduardoN	[e-mail]
Jean Hayes	@jehayesms	[e-mail]
Marco Aurélio Bigélli Cardoso	@MarcoABCardoso	[e-mail]
Maria Vrabie	@MariaVrabie	[e-mail]
Neeraj Jhaveri	@neerajjhaveri	[e-mail]
Thiago Rotta	@rottathiago	[e-mail]
Victor Santana	@Welasco	[e-mail]