AI automation is central to realising productivity improvements for CRM, SFA and in ensuring that data is relevant, clean and appropriate for the use case. Cloud native AI including Azure ML and AI; AWS AI and Google (Colab) are used.
Azure AI and ML Services, Use Cases, and Architectures
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AI automation within Azure and between Azure and Dynamics or other SaaS applications and platforms can greatly enhance productivity and data usage to generate revenues or reduce costs.
Use Cases include:
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AWS has similar AI capabilities which can be aligned with CRM, SFA and client data. Machine Learning, analysis, new data product creation and data cleansing are some important areas where AI can enhance the architecture.
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For CRM, SFA or applications in general, it is recommended to move to a Low Code, No Code target model.
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AI process within CRM, SFA automation, optimisation
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Add new functionality to an existing React.js application, serving B2B customers, but do not re-engineer the application
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