diff --git a/examples/nodejs/examples/embed/index.ts b/examples/nodejs/examples/embed/index.ts
new file mode 100644
index 0000000..1abc06e
--- /dev/null
+++ b/examples/nodejs/examples/embed/index.ts
@@ -0,0 +1,22 @@
+import 'dotenv/config';
+import {Langbase} from 'langbase';
+
+const langbase = new Langbase({
+	apiKey: process.env.LANGBASE_API_KEY!,
+});
+
+/**
+ * Generates embeddings for the given text chunks.
+ */
+async function main() {
+	const response = await langbase.embed({
+		chunks: [
+			'Langbase is the most powerful serverless platform for building AI agents with memory. Build, scale, and evaluate AI agents with semantic memory (RAG) and world-class developer experience. We process billions of AI messages/tokens daily. Built for every developer, not just AI/ML experts.',
+		],
+		embeddingModel: 'openai:text-embedding-3-large',
+	});
+
+	console.log(response);
+}
+
+main();
diff --git a/examples/nodejs/package.json b/examples/nodejs/package.json
index 422a799..fcbda8c 100644
--- a/examples/nodejs/package.json
+++ b/examples/nodejs/package.json
@@ -29,7 +29,8 @@
     "stream-text-generate-pipe": "npx tsx ./examples/pipes/stream-text-generate-pipe.ts",
     "stream-text-chat-pipe": "npx tsx ./examples/pipes/stream-text-chat-pipe.ts",
     "tools.web-search": "npx tsx ./examples/tools/web-search.ts",
-    "tools.crawl": "npx tsx ./examples/tools/crawl.ts"
+    "tools.crawl": "npx tsx ./examples/tools/crawl.ts",
+    "embed": "npx tsx ./examples/embed/index.ts"
   },
   "keywords": [],
   "author": "Ahmad Awais <me@AhmadAwais.com> (https://twitter.com/MrAhmadAwais)",
diff --git a/packages/langbase/src/langbase/langbase.ts b/packages/langbase/src/langbase/langbase.ts
index 8e47f0c..5a07564 100644
--- a/packages/langbase/src/langbase/langbase.ts
+++ b/packages/langbase/src/langbase/langbase.ts
@@ -272,6 +272,13 @@ export interface ToolCrawlResponse {
 	content: string;
 }
 
+export interface EmbedOptions {
+	chunks: string[];
+	embeddingModel?: EmbeddingModels;
+}
+
+export type EmbedResponse = number[][];
+
 export class Langbase {
 	private request: Request;
 	private apiKey: string;
@@ -314,6 +321,8 @@ export class Langbase {
 		) => Promise<ToolWebSearchResponse[]>;
 	};
 
+	public embed: (options: EmbedOptions) => Promise<EmbedResponse>;
+
 	constructor(options?: LangbaseOptions) {
 		const baseUrl = 'https://api.langbase.com';
 		this.apiKey = options?.apiKey ?? '';
@@ -347,6 +356,8 @@ export class Langbase {
 			crawl: this.webCrawl.bind(this),
 			webSearch: this.webSearch.bind(this),
 		};
+
+		this.embed = this.generateEmbeddings.bind(this);
 	}
 
 	private async runPipe(
@@ -607,4 +618,19 @@ export class Langbase {
 			},
 		});
 	}
+
+	/**
+	 * Generates embeddings for the given input using the LangBase API.
+	 *
+	 * @param options - Embed options
+	 * @returns Promise that resolves to the embedding response containing vector representations
+	 */
+	private async generateEmbeddings(
+		options: EmbedOptions,
+	): Promise<EmbedResponse> {
+		return this.request.post({
+			endpoint: '/v1/embed',
+			body: options,
+		});
+	}
 }