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@@ -0,0 +1,7 @@
+---
+type: docs
+title: "AI"
+linkTitle: "AI"
+weight: 3000
+description: With the Dapr Conversation AI package, you can interact with the Dapr AI workloads from a Java application. To get started, walk through the [Dapr AI]({{< ref java-ai-howto.md >}}) how-to guide.
+---
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diff --git a/daprdocs/content/en/java-sdk-docs/java-ai/java-ai-howto.md b/daprdocs/content/en/java-sdk-docs/java-ai/java-ai-howto.md
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+---
+type: docs
+title: "How to: Author and manage Dapr Conversation AI in the Java SDK"
+linkTitle: "How to: Author and manage Conversation AI"
+weight: 20000
+description: How to get up and running with Conversation AI using the Dapr Java SDK
+---
+
+As part of this demonstration, we will look at how to use the Conversation API to converse with a Large Language Model (LLM). The API
+will return the response from the LLM for the given prompt. With the [provided conversation ai example](https://github.com/dapr/java-sdk/tree/master/examples/src/main/java/io/dapr/examples/conversation), you will:
+
+- You will provide a prompt using the [Conversation AI example](https://github.com/dapr/java-sdk/blob/master/examples/src/main/java/io/dapr/examples/conversation/DemoConversationAI.java)
+- Filter out Personally identifiable information (PII).
+
+This example uses the default configuration from `dapr init` in [self-hosted mode](https://github.com/dapr/cli#install-dapr-on-your-local-machine-self-hosted).
+
+## Prerequisites
+
+- [Dapr CLI and initialized environment](https://docs.dapr.io/getting-started).
+- Java JDK 11 (or greater):
+  - [Oracle JDK](https://www.oracle.com/java/technologies/downloads), or
+  - OpenJDK
+- [Apache Maven](https://maven.apache.org/install.html), version 3.x.
+- [Docker Desktop](https://www.docker.com/products/docker-desktop)
+
+## Set up the environment
+
+Clone the [Java SDK repo](https://github.com/dapr/java-sdk) and navigate into it.
+
+```bash
+git clone https://github.com/dapr/java-sdk.git
+cd java-sdk
+```
+
+Run the following command to install the requirements for running the Conversation AI example with the Dapr Java SDK.
+
+```bash
+mvn clean install -DskipTests
+```
+
+From the Java SDK root directory, navigate to the examples' directory.
+
+```bash
+cd examples
+```
+
+Run the Dapr sidecar.
+
+```sh
+dapr run --app-id conversationapp --dapr-grpc-port 51439 --dapr-http-port 3500 --app-port 8080
+```
+
+> Now, Dapr is listening for HTTP requests at `http://localhost:3500` and gRPC requests at `http://localhost:51439`.
+
+## Send a prompt with Personally identifiable information (PII) to the Conversation AI API
+
+In the `DemoConversationAI` there are steps to send a prompt using the `converse` method under the `DaprPreviewClient`.
+
+```java
+public class DemoConversationAI {
+  /**
+   * The main method to start the client.
+   *
+   * @param args Input arguments (unused).
+   */
+  public static void main(String[] args) {
+    try (DaprPreviewClient client = new DaprClientBuilder().buildPreviewClient()) {
+      System.out.println("Sending the following input to LLM: Hello How are you? This is the my number 672-123-4567");
+
+      ConversationInput daprConversationInput = new ConversationInput("Hello How are you? "
+              + "This is the my number 672-123-4567");
+
+      // Component name is the name provided in the metadata block of the conversation.yaml file.
+      Mono<ConversationResponse> responseMono = client.converse(new ConversationRequest("echo",
+              List.of(daprConversationInput))
+              .setContextId("contextId")
+              .setScrubPii(true).setTemperature(1.1d));
+      ConversationResponse response = responseMono.block();
+      System.out.printf("Conversation output: %s", response.getConversationOutputs().get(0).getResult());
+    } catch (Exception e) {
+      throw new RuntimeException(e);
+    }
+  }
+}
+```
+
+Run the `DemoConversationAI` with the following command.
+
+```sh
+java -jar target/dapr-java-sdk-examples-exec.jar io.dapr.examples.conversation.DemoConversationAI
+```
+
+### Sample output
+```
+== APP == Conversation output: Hello How are you? This is the my number <ISBN>
+```
+
+As shown in the output, the number sent to the API is obfuscated and returned in the form of <ISBN>.
+The example above uses an ["echo"](https://docs.dapr.io/developing-applications/building-blocks/conversation/howto-conversation-layer/#set-up-the-conversation-component)
+component for testing, which simply returns the input message.
+When integrated with LLMs like OpenAI or Claude, you’ll receive meaningful responses instead of echoed input.
+
+## Next steps
+- [Learn more about Conversation AI]({{< ref conversation-overview.md >}})
+- [Conversation AI API reference]({{< ref conversation_api.md >}})
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diff --git a/daprdocs/content/en/java-sdk-docs/java-jobs/java-jobs-howto.md b/daprdocs/content/en/java-sdk-docs/java-jobs/java-jobs-howto.md
index 1aa8f7b91..f68a2f8d5 100644
--- a/daprdocs/content/en/java-sdk-docs/java-jobs/java-jobs-howto.md
+++ b/daprdocs/content/en/java-sdk-docs/java-jobs/java-jobs-howto.md
@@ -38,7 +38,7 @@ Run the following command to install the requirements for running the jobs examp
 mvn clean install -DskipTests
 ```
 
-From the Java SDK root directory, navigate to the Dapr Jobs example.
+From the Java SDK root directory, navigate to the examples' directory.
 
 ```bash
 cd examples