Customize Amazon Q in Connect
You can customize how Amazon Q in Connect works by using the Amazon Connect admin website, no coding required. For example, you can customize the tone or format of the responses, the language, or the behavior.
Following are a few use cases for how you can customize Amazon Q in Connect:
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Personalize a response based on data. For example, you want Amazon Q in Connect to provide a recommendation to a caller based on their loyalty status and past purchase history.
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Make responses more empathetic because of the line of business that it's in.
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Create a new tool, such as a self-service password reset for customers.
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Summarize a conversation and pass it to an agent.
You customize Amazon Q in Connect by creating or editing AI prompts, AI guardrails, and AI agents.
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AI prompt: This is a task for the large language model (LLM) to do. It provides a task description or instruction for how the model should perform. For example, Given a list of customer orders and available inventory, determine which orders can be fulfilled and which items have to be restocked.
To make it easy for non-developers to create AI prompts, Amazon Q in Connect provides a set of templates that already contain instructions. The templates contain placeholder instructions written in an easy-to-understand language called YAML. You just replace the placeholder instructions with your own instructions.
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AI guardrail: Safeguards based on your use cases and responsible AI policies. Guardrails filter harmful and inappropriate responses, redact sensitive personal information, and limit incorrect information in the responses due to potential LLM hallucination.
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AI agent: An Amazon Q in Connect resource that configures and customizes end-to-end Amazon Q in Connect functionality. AI agents determine which AI prompts and AI guardrails are used in different use cases: answer recommendations, manual search, and self-service.
You can edit or create each of these components independently of each other. However, we recommend a happy path where you first customize your AI prompts and/or AI guardrails. Then add them to your AI agents. Finally create a Lambda and use the Invoke AWS Lambda function block to associate the customized AI agents with your flows.
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