Customize Amazon Quick embedded chat into your application
Amazon Quick embedded chat brings a conversational AI interface into your web application. This post walks through customizing the embedded chat with container and SDK styling, branding removal, and a custom agent persona so it matches your brand's look, feel, and voice.
Amazon Quick embedded chat offers a conversational AI interface that you can integrate into your web application. This allows users to ask questions, explore data, and receive insights without leaving your application. However, a generic chat interface can create a disjointed user experience. To provide a consistent and branded experience, you can customize the Quick chat to match your application's visual theme and communication style.
Customization typically involves two main areas: visual theming and tone. Visual theming requires matching the chat interface to your company's brand guidelines. This includes adjusting the color palette, branding elements, and overall design to blend seamlessly with your application. The embedding SDK provides options for container and layout styling, as well as frame options to control the chat iframe behavior.
By applying custom CSS classes, adjusting dimensions, and removing default branding elements like the "Powered by" text and usage policy link, you can make the chat feel like a native part of your application.
Tone customization is equally important. The way the chat communicates should reflect your organization's personality and communication style. Without a custom chat agent, the responses will be generic and lack organizational context. To address this, you can configure the chat to adopt a specific persona that aligns with your company's voice. This ensures that the chat responses are tailored to your organization's communication style and domain expertise.
In summary, by customizing the visual theming and tone of Amazon Quick embedded chat, you can deliver a consistent and branded experience within your application. This enhances user engagement and provides a seamless, integrated experience for your users.
Written by urgent.news from AWS Machine Learning's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.