1. Azure AutoML for customizing and optimizing the models for your specific needs and scenarios.
2. Azure Language Service for accessing a suite of natural language processing capabilities, such as text analysis, translation, speech recognition, and synthesis.
3. Azure OpenAI gpt-35-turbo-16k for generating natural language text for transcript summarization, correspondence composition, case classification, offensive language masking, and data analytics and modeling. gpt-35-turbo-16kis a powerful and versatile language model that can adapt to various domains and tasks with minimal data and supervision.
4. Azure Form Recognizer for extracting structured data from unstructured documents, such as invoices, receipts, forms, etc. Form Recognizer can also mask sensitive data and validate document completeness.
5. PowerBI for visualizing and reporting the data analytics results in interactive dashboards and charts.
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1. Prepare suggested volume of sample data for each AI area that need to be trained by Council for the AI models during the development stage as per AI-1 and AI-7 1.
2. Specify estimated resources required from Council in maintaining the azure openai and data training with embedding after the system launch such as update/training frequency, volume of data required, staff effort required, time required, related running cost, etc. as per AI-7 1.
3. Explore potential use of AI for the new system and ways to adapt AI growth in the future considering rapid changes in AI as per AI-7a 1.

1. Availability of requisite data required for model development.
2. The scope may be adjusted at various stages based on feasibility and utility.