diff --git a/docs/remote_inference_blueprints/standard_blueprints/README.md b/docs/remote_inference_blueprints/standard_blueprints/README.md
index de255061eb..4f84b1d8c4 100644
--- a/docs/remote_inference_blueprints/standard_blueprints/README.md
+++ b/docs/remote_inference_blueprints/standard_blueprints/README.md
@@ -22,6 +22,8 @@ These blueprints use the ML inference processor to handle input/output mapping,
   - image embedding: [embed-multimodal-v3.0 & embed-multimodal-v2.0](https://github.com/opensearch-project/ml-commons/blob/main/docs/remote_inference_blueprints/standard_blueprints/cohere_connector_image_embedding_blueprint.md)
 - OpenAI:
   - [text-embedding-ada-002](https://github.com/opensearch-project/ml-commons/blob/main/docs/remote_inference_blueprints/standard_blueprints/openai_connector_embedding_standard_blueprint.md)
+- Yandex Cloud:
+  - text embedding: [text-search-doc & text-search-query](https://github.com/opensearch-project/ml-commons/blob/main/docs/remote_inference_blueprints/standard_blueprints/yandexcloud_connector_embedding_standard_blueprint.md) 
 
 ## Legacy Blueprints (With Pre/Post Processing)
 For existing implementations or specific customization needs
diff --git a/docs/remote_inference_blueprints/standard_blueprints/yandexcloud_connector_embedding_standard_blueprint.md b/docs/remote_inference_blueprints/standard_blueprints/yandexcloud_connector_embedding_standard_blueprint.md
new file mode 100644
index 0000000000..df4bc10cca
--- /dev/null
+++ b/docs/remote_inference_blueprints/standard_blueprints/yandexcloud_connector_embedding_standard_blueprint.md
@@ -0,0 +1,138 @@
+# Yandex Cloud AI Studio connector standard blueprint example for embedding models
+
+This blueprint demonstrates how to deploy a Yandex Cloud AI Studio embedding models. 
+
+## 1. Allow connection to Yandex Cloud
+
+```json
+PUT /_cluster/settings
+{
+  "persistent": {
+    "plugins.ml_commons.trusted_connector_endpoints_regex": [
+      "^https://llm\\.api\\.cloud\\.yandex\\.net/.*$"
+    ]
+  }
+}
+```
+
+## 2. Create connector for Yandex Cloud Embeddings:
+
+
+```json
+POST /_plugins/_ml/connectors/_create
+{
+  "name": "YC Connector: embedding",
+  "description": "Yandex Cloud AI Studio Embeddings",
+  "version": "1",
+  "protocol": "http",
+  "parameters": {
+    "modelUri": "emb://<folder_ID>/text-search-<doc|query>/latest",
+    "folder_id":"<folder_ID>"
+  },
+  "credential": {
+    "api_key": "<API-KEY>"
+  },
+  "actions": [
+    {
+      "action_type": "predict",
+      "method": "POST",
+      "url": "https://llm.api.cloud.yandex.net/foundationModels/v1/textEmbedding",
+      "headers": {
+        "Authorization": "Api-Key ${credential.api_key}",
+        "x-folder-id": "${parameters.folder_id}"
+      },
+      "request_body": "{ \"text\": \"${parameters.inputText}\", \"modelUri\": \"${parameters.modelUri}\" }",
+      "pre_process_function": "connector.pre_process.bedrock.embedding",
+      "post_process_function": "connector.post_process.bedrock.embedding"
+    }
+  ]
+}
+```
+
+Note: Replace all `<placeholders>` in the preceding code snippet with appropriate values, while preserving `${curly braces}` syntax exactly as shown. Short-lived [bearer tokens](https://yandex.cloud/en/docs/iam/concepts/authorization/iam-token) (valid ~12 hours) may be used as an alternative to [API keys](https://yandex.cloud/en/docs/iam/concepts/authorization/api-key). API keys must be granted either `yc.ai.languageModels.execute` or `yc.ai.foundationModels.execute` roles. Also refer to [the guide](https://yandex.cloud/en/docs/ai-studio/security/). Additionally, due to distinct [models](https://yandex.cloud/en/docs/ai-studio/concepts/embeddings) being employed for query processing versus document processing, two dedicated connectors are required. Using these particular pre/post processing functions is crucial.  
+
+Sample response:
+```json
+{
+    "connector_id": "CTEou5oBdUNOOrVArUAU"
+}
+```
+
+## 3. Register model & deploy model:
+
+```json
+POST /_plugins/_ml/model_groups/_register
+{
+  "name": "yc_remote_model_group",
+  "description": "A model group for external YC AI Studio models"
+}
+```
+
+Sample response:
+```json
+{
+    "model_group_id": "4THNtZoBdUNOOrVAzj_V"
+}
+```
+
+```json
+POST /_plugins/_ml/models/_register
+{
+    "name": "yc-embedding",
+    "function_name": "remote",
+    "model_group_id": "4THNtZoBdUNOOrVAzj_V",
+    "description": "YC embedding model",
+    "connector_id": "CTEou5oBdUNOOrVArUAU"
+}
+```
+
+Sample response:
+```json
+{
+  "task_id": "5THZtZoBdUNOOrVAEj_I",
+  "status": "CREATED",
+  "model_id": "CzEou5oBdUNOOrVA10Db"
+}
+```
+
+## 4. Test model inference
+
+```json
+POST /_plugins/_ml/models/CzEou5oBdUNOOrVA10Db/_predict
+{
+  "parameters": {
+    "inputText": "What is the meaning of life?"
+  }
+}
+```
+
+Sample response of Yandex Cloud AI Studio Embedding:
+
+```json
+{
+  "inference_results": [
+    {
+      "output": [
+        {
+          "name": "sentence_embedding",
+          "data_type": "FLOAT32",
+          "shape": [
+            256
+          ],
+          "data": [
+            0.06268310546875,
+            -0.04071044921875,
+            0.047119140625,
+            -0.007476806640625,
+            -0.038543701171875,
+            -0.003681182861328125,
+            ...
+            0.040679931640625
+          ]
+        }
+      ],
+      "status_code": 200
+    }
+  ]
+}
+```