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1.1 Application Scenario

To simplify our walkthrough, we'll use the same Application Scenario and Application Data resources defined in the Hybrid Workshop path.

  • See: Contoso Outdoor to understand the enterprise retail application scenario.
  • See: Application Data to understand customer, product & manual data formats.

Contoso Chat

Assume that you are building the retail copilot chat AI (backend) that can be accessed from the Contoso Outdoor UI (frontend) shown below. Your chat AI needs to do the following:

  • Answer customer queries in natural language (= generative AI)
  • Give answers grounded in product data (= RAG design pattern)
  • Give answers that are also coherent, fluent & relevant (= evaluators)
  • Block customer requests that have harmful intent (= content safety)
  • Block customer requests that break the rules (= jailbreak protection)