Adobe LLM Apps - An Overview adobe-llm-apps-an-overview

IMPORTANT
Adobe LLM Apps is currently in Beta.
Features, workflows, and UI shown here do not necessarily represent the final state of the product. To join the Beta, send an email to llm-apps-beta@adobe.com.

What is Adobe LLM Apps?

Adobe LLM Apps lets your brand offer useful actions—such as product discovery, availability checks, or service bookings—inside supported AI assistants such as ChatGPT and Claude.

LLM Apps is available at experience.adobe.com/llm-apps.

What you can do with LLM Apps

  • Create brand-owned LLM actions — Define the specific business flows you want to activate inside AI assistants (for example, Schedule a Test Drive, Compare Products, Book a Service).
  • Build interactive LLM widgets — Create visual UI components (product cards, booking forms, store locators) managed as AEM components in your GitHub repository.
  • Maintain centralized brand governance — Authors and developers retain full control over all content, copy, and visuals exposed inside the LLM platform, with approvals managed through AEM.
  • Deploy to staging and production — A controlled deployment pipeline lets you test the experience in a staging environment before promoting to production.
  • Control visibility at the action level — Enable or disable individual actions, then deploy the app to apply the change.
  • Measure what drives decisions — Built-in analytics (powered by Adobe Customer Journey Analytics) surface action trigger counts, success rates, abandonment rates, top user prompts, and visibility scores.

Why LLM Apps matter

LLM interactions are fundamentally different from traditional search. The average LLM session lasts four times longer than a traditional search session. More than 40% of consumers rely on AI tools for complex purchase decisions. Without LLM Apps, you might win the mention but lose the customer. LLM Apps ensures your brand is not just visible but actionable at the exact moment a user is ready to decide.

Key concepts key-concepts

LLM App

Your branded assistant that users interact with inside ChatGPT or other LLM platforms. It groups together all your actions and deploys as a single unit.

Action actions

A capability your app offers, such as Find a distributor or Browse products. The LLM platform invokes an action when a request matches its description. LLM Apps manages action metadata, and the GitHub repository stores the handler code.

Action handler

The server-side function that runs when the LLM platform invokes an action. Use the handler to validate input, call your APIs, and return text plus structured data.

Widget widgets-eds

The visual response shown with the LLM’s reply, such as a card, carousel, or table. Generated widgets are blocks in an Edge Delivery Services (EDS) repository. With Adobe managed infrastructure, Adobe prepares and hosts the repository for you. Alternatively, connect your own repository.

MCP server

The endpoint exposed after deployment. A supported LLM platform connects to this endpoint to discover and invoke your actions.

How it works

You define your brand’s capabilities in LLM Apps. The platform makes those capabilities available as actions, and an AI assistant uses the actions to answer customer requests in the conversation.

┌────────────────────┐          ┌────────────────────┐          ┌────────────────────┐
│     Your brand     │          │      LLM Apps      │          │    AI assistant    │
│                    │          │                    │          │                    │
│   What you offer   │   ───▶   │  Turns that into   │   ───▶   │ Answers with your  │
│  and how you help  │          │    something AI    │          │    brand, live     │
│  customers today   │          │     can act on     │          │  inside the chat   │
└────────────────────┘          └────────────────────┘          └────────────────────┘

For technical details about what to build and how the components work together, see How an app is wired together.

Get started choose-your-journey

Creating an app and creating its actions are separate steps:

  1. Set up the infrastructure. Use Adobe managed infrastructure for a quick setup, or choose to use your own GitHub repositories.
  2. Create your actions. Have the platform analyze your website and generate actions, or create them yourself.
  3. Deploy and test the app. Review the generated work, deploy to Stage, and test in a supported LLM platform.

Automatic generation gives you a starting point with sample behavior. Before making the app available to customers, connect your handlers to your systems and customize the widgets.

To report on your app in your own Adobe Analytics or Customer Journey Analytics, see Set up Adobe Analytics and Customer Journey Analytics.

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