Repository: kaito-project/kaito

Issue:
docs: Acronym alignment
See https://github.com/kaito-project/kaito/pull/1123. Let's ensure consistency when using `KAITO` acronym.

Discussion:

Solution patch:
diff --git a/Makefile b/Makefile
index 9d7d887..b2d7ac4 100644
--- a/Makefile
+++ b/Makefile
@@ -175,7 +175,7 @@ $(RAGENGINE_E2E_TEST): ## Build the RAG Engine e2e test binary without running i
 	(cd test/rage2e && go test -c . -o $(RAGENGINE_E2E_TEST))
 
 .PHONY: kaito-workspace-e2e-test
-kaito-workspace-e2e-test: $(E2E_TEST) $(GINKGO) ## Run e2e tests for Kaito Workspace.
+kaito-workspace-e2e-test: $(E2E_TEST) $(GINKGO) ## Run e2e tests for KAITO Workspace.
 	AI_MODELS_REGISTRY_SECRET=$(AI_MODELS_REGISTRY_SECRET) \
  	AI_MODELS_REGISTRY=$(AI_MODELS_REGISTRY) GPU_PROVISIONER_NAMESPACE=$(GPU_PROVISIONER_NAMESPACE) GPU_PROVISIONER_NAME=$(GPU_PROVISIONER_NAME) \
  	KARPENTER_NAMESPACE=$(KARPENTER_NAMESPACE) KAITO_NAMESPACE=$(KAITO_NAMESPACE) TEST_SUITE=$(TEST_SUITE) \
@@ -183,7 +183,7 @@ kaito-workspace-e2e-test: $(E2E_TEST) $(GINKGO) ## Run e2e tests for Kaito Works
  	$(GINKGO) -v -trace $(GINKGO_ARGS) $(E2E_TEST)
 
 .PHONY: kaito-ragengine-e2e-test
-kaito-ragengine-e2e-test: $(RAGENGINE_E2E_TEST) $(GINKGO) ## Run e2e tests for Kaito RAG Engine.
+kaito-ragengine-e2e-test: $(RAGENGINE_E2E_TEST) $(GINKGO) ## Run e2e tests for KAITO RAG Engine.
 	AI_MODELS_REGISTRY_SECRET=$(AI_MODELS_REGISTRY_SECRET) \
 	AI_MODELS_REGISTRY=$(AI_MODELS_REGISTRY) GPU_PROVISIONER_NAMESPACE=$(GPU_PROVISIONER_NAMESPACE)  GPU_PROVISIONER_NAME=$(GPU_PROVISIONER_NAME) KAITO_NAMESPACE=$(KAITO_NAMESPACE) \
 	KARPENTER_NAMESPACE=$(KARPENTER_NAMESPACE) KAITO_RAGENGINE_NAMESPACE=$(KAITO_RAGENGINE_NAMESPACE) TEST_SUITE=$(TEST_SUITE) \
@@ -214,7 +214,7 @@ create-aks-cluster: ## Create an AKS cluster with MSI, OIDC, and workload identi
 	az aks get-credentials --name $(AZURE_CLUSTER_NAME) --resource-group $(AZURE_RESOURCE_GROUP) --overwrite-existing
 
 .PHONY: create-aks-cluster-with-kaito
-create-aks-cluster-with-kaito: ## Create an AKS cluster with MSI, OIDC, and Kaito enabled.
+create-aks-cluster-with-kaito: ## Create an AKS cluster with MSI, OIDC, and KAITO enabled.
 	az aks create  --name $(AZURE_CLUSTER_NAME) --resource-group $(AZURE_RESOURCE_GROUP) \
 	--location $(AZURE_LOCATION) --attach-acr $(AZURE_ACR_NAME) \
 	--kubernetes-version $(AKS_K8S_VERSION) --generate-ssh-keys  \
@@ -372,13 +372,13 @@ docker-build-llm-reference-preset: docker-buildx ## Build Docker image for LLM r
 		--build-arg VERSION=$(VERSION) .
 
 ## --------------------------------------
-## Kaito Installation
+## KAITO Installation
 ## --------------------------------------
 
-##@ Kaito Installation
+##@ KAITO Installation
 
 .PHONY: prepare-kaito-addon-identity
-prepare-kaito-addon-identity: ## Create Azure identity and federated credential for Kaito addon.
+prepare-kaito-addon-identity: ## Create Azure identity and federated credential for KAITO addon.
 	IDENTITY_PRINCIPAL_ID=$(shell az identity show --name "ai-toolchain-operator-$(AZURE_CLUSTER_NAME)" -g "$(AZURE_RESOURCE_GROUP_MC)"  --query 'principalId');\
 	az role assignment create --assignee $$IDENTITY_PRINCIPAL_ID --scope "/subscriptions/$(AZURE_SUBSCRIPTION_ID)/resourceGroups/$(AZURE_RESOURCE_GROUP_MC)"  --role "Contributor"
 
@@ -388,7 +388,7 @@ prepare-kaito-addon-identity: ## Create Azure identity and federated credential
     --subject system:serviceaccount:"$(KAITO_NAMESPACE):kaito-gpu-provisioner" --audience api://AzureADTokenExchange
 
 .PHONY: az-patch-install-helm
-az-patch-install-helm: ## Install Kaito workspace Helm chart and set Azure client env vars and settings in Helm values.
+az-patch-install-helm: ## Install KAITO workspace Helm chart and set Azure client env vars and settings in Helm values.
 	az aks get-credentials --name $(AZURE_CLUSTER_NAME) --resource-group $(AZURE_RESOURCE_GROUP)
 
 	yq -i '(.image.repository)                                              = "$(REGISTRY)/workspace"'                    ./charts/kaito/workspace/values.yaml
@@ -398,7 +398,7 @@ az-patch-install-helm: ## Install Kaito workspace Helm chart and set Azure clien
 	helm install kaito-workspace ./charts/kaito/workspace --namespace $(KAITO_NAMESPACE) --create-namespace $(HELM_INSTALL_EXTRA_ARGS)
 
 .PHONY: az-patch-install-ragengine-helm
-az-patch-install-ragengine-helm: ## Install Kaito RAG Engine Helm chart and set Azure client env vars and settings in Helm values.
+az-patch-install-ragengine-helm: ## Install KAITO RAG Engine Helm chart and set Azure client env vars and settings in Helm values.
 	az aks get-credentials --name $(AZURE_CLUSTER_NAME) --resource-group $(AZURE_RESOURCE_GROUP)
 
 	yq -i '(.image.repository)                                              = "$(REGISTRY)/ragengine"'                    ./charts/kaito/ragengine/values.yaml
@@ -408,7 +408,7 @@ az-patch-install-ragengine-helm: ## Install Kaito RAG Engine Helm chart and set
 	helm install kaito-ragengine ./charts/kaito/ragengine --namespace $(KAITO_RAGENGINE_NAMESPACE) --create-namespace $(HELM_INSTALL_EXTRA_ARGS)
 
 .PHONY: az-patch-install-ragengine-helm-e2e
-az-patch-install-ragengine-helm-e2e: ## Install Kaito RAG Engine Helm chart for e2e tests and set Azure client env vars and settings in Helm values.
+az-patch-install-ragengine-helm-e2e: ## Install KAITO RAG Engine Helm chart for e2e tests and set Azure client env vars and settings in Helm values.
 	az aks get-credentials --name $(AZURE_CLUSTER_NAME) --resource-group $(AZURE_RESOURCE_GROUP)
 
 	yq -i '(.image.repository)                                              = "$(REGISTRY)/ragengine"'                    ./charts/kaito/ragengine/values.yaml
@@ -421,7 +421,7 @@ az-patch-install-ragengine-helm-e2e: ## Install Kaito RAG Engine Helm chart for
 	helm install kaito-ragengine ./charts/kaito/ragengine --namespace $(KAITO_RAGENGINE_NAMESPACE) --create-namespace $(HELM_INSTALL_EXTRA_ARGS)
 
 .PHONY: aws-patch-install-helm
-aws-patch-install-helm: ## Install Kaito workspace Helm chart and set AWS env vars and settings in Helm values.
+aws-patch-install-helm: ## Install KAITO workspace Helm chart and set AWS env vars and settings in Helm values.
 	yq -i '(.image.repository)                                              = "$(REGISTRY)/workspace"'                    	./charts/kaito/workspace/values.yaml
 	yq -i '(.image.tag)                                                     = "$(IMG_TAG)"'                               	./charts/kaito/workspace/values.yaml
 	yq -i '(.clusterName)                                                   = "$(AWS_CLUSTER_NAME)"'                    		./charts/kaito/workspace/values.yaml
diff --git a/README.md b/README.md
index 22205d7..d5723a4 100644
--- a/README.md
+++ b/README.md
@@ -149,7 +149,7 @@ Linux Foundation ID group through the [Linux Foundation Support website](https:/
 
 ## Get Involved!
 
-- Visit [#kaito channel in CNCF Slack](https://cloud-native.slack.com/archives/C09B4EWCZ5M) to discuss features in development and proposals.
+- Visit [#KAITO channel in CNCF Slack](https://cloud-native.slack.com/archives/C09B4EWCZ5M) to discuss features in development and proposals.
 - We host a weekly community meeting for contributors on Tuesdays at 4:00pm PST. Please join here: [meeting link](https://zoom-lfx.platform.linuxfoundation.org/meeting/99948431028?password=05912bb9-53fb-4b22-a634-ab5f8261e94c).
 - Reference the weekly meeting notes in our [KAITO community calls doc](https://docs.google.com/document/d/1OEC-WUQ2wn0TDQPsU09shMoXn5cW3dSrdu-M43Q79dA/edit?usp=sharing)!
 
diff --git a/api/v1alpha1/doc.go b/api/v1alpha1/doc.go
index 634b6dc..9a6d9ab 100644
--- a/api/v1alpha1/doc.go
+++ b/api/v1alpha1/doc.go
@@ -11,7 +11,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-// Package v1alpha1 contains API Schema definitions for the kaito v1alpha1 API group
+// Package v1alpha1 contains API Schema definitions for the KAITO v1alpha1 API group
 // +kubebuilder:object:generate=true
 // +k8s:defaulter-gen=TypeMeta
 // +groupName=kaito.sh
diff --git a/api/v1alpha1/labels.go b/api/v1alpha1/labels.go
index c70bdd0..9120a93 100644
--- a/api/v1alpha1/labels.go
+++ b/api/v1alpha1/labels.go
@@ -26,7 +26,7 @@ const (
 	// KAITOPrefix Kubernetes Data Mining prefix.
 	KAITOPrefix = "kaito.sh/"
 
-	// AnnotationEnableLB determines whether kaito creates LoadBalancer type service for testing.
+	// AnnotationEnableLB determines whether KAITO creates LoadBalancer type service for testing.
 	AnnotationEnableLB = KAITOPrefix + "enablelb"
 
 	// LabelWorkspaceName is the label for workspace name.
diff --git a/api/v1beta1/labels.go b/api/v1beta1/labels.go
index 1b01406..84f6837 100644
--- a/api/v1beta1/labels.go
+++ b/api/v1beta1/labels.go
@@ -26,7 +26,7 @@ const (
 	// KAITOPrefix Kubernetes Data Mining prefix.
 	KAITOPrefix = "kaito.sh/"
 
-	// AnnotationEnableLB determines whether kaito creates LoadBalancer type service for testing.
+	// AnnotationEnableLB determines whether KAITO creates LoadBalancer type service for testing.
 	AnnotationEnableLB = KAITOPrefix + "enablelb"
 
 	// LabelWorkspaceName is the label for workspace name.
diff --git a/charts/kaito/ragengine/values.yaml b/charts/kaito/ragengine/values.yaml
index 0e662a3..12946bf 100644
--- a/charts/kaito/ragengine/values.yaml
+++ b/charts/kaito/ragengine/values.yaml
@@ -1,4 +1,4 @@
-# Default values for kaito.
+# Default values for KAITO.
 # This is a YAML-formatted file.
 # Declare variables to be passed into your templates.
 replicaCount: 1
diff --git a/charts/kaito/workspace/values.yaml b/charts/kaito/workspace/values.yaml
index 68e3228..df2d938 100644
--- a/charts/kaito/workspace/values.yaml
+++ b/charts/kaito/workspace/values.yaml
@@ -1,4 +1,4 @@
-# Default values for kaito.
+# Default values for KAITO.
 # This is a YAML-formatted file.
 # Declare variables to be passed into your templates.
 replicaCount: 1
diff --git a/docs/documentation-versioning.md b/docs/documentation-versioning.md
index 376e90f..885c638 100644
--- a/docs/documentation-versioning.md
+++ b/docs/documentation-versioning.md
@@ -1,10 +1,10 @@
 # Documentation Versioning Workflow
 
-This document explains how the automated documentation versioning workflow works in the Kaito project.
+This document explains how the automated documentation versioning workflow works in the KAITO project.
 
 ## Overview
 
-The `docs-versioning.yaml` GitHub Actions workflow automatically creates versioned documentation when new minor versions are released. This ensures that users can access documentation for specific versions of Kaito.
+The `docs-versioning.yaml` GitHub Actions workflow automatically creates versioned documentation when new minor versions are released. This ensures that users can access documentation for specific versions of KAITO.
 
 ## How it Works
 
diff --git a/docs/proposals/20250611-workspace-subresource-scale-api.md b/docs/proposals/20250611-workspace-subresource-scale-api.md
index 63990c0..b937996 100644
--- a/docs/proposals/20250611-workspace-subresource-scale-api.md
+++ b/docs/proposals/20250611-workspace-subresource-scale-api.md
@@ -14,24 +14,24 @@ see-also:
 
 # Title
 
-Support scale subresource api for workspace in kaito
+Support scale subresource api for workspace in KAITO
 
 ## Summary
 
 As the number of waiting inference requests increase, It is necessary to scale more inference instances in order to preventing to block inference requests. on the other hand, If the number of waiting inference requests declines, we should consider to reduce inference instances for improving gpu resource utilization.
 
-We hope to provide an auto-scaler feature for scaling inference workloads automatically in terms of changes of custom metrics from inference pods, and this auto scaler doesn't depend on other components(this means Kaito is a self-contained component without dependencies). and we will divide this auto-scaler feature into two parts as following:
+We hope to provide an auto-scaler feature for scaling inference workloads automatically in terms of changes of custom metrics from inference pods, and this auto scaler doesn't depend on other components(this means KAITO is a self-contained component without dependencies). and we will divide this auto-scaler feature into two parts as following:
 
-- Part one: support scale subresource api for workspace, so different auto-scaler solutions such as KEDA, HPA, etc. can be integrated with Kaito to mamage inference workloads dynamically. This part is addressed in this proposal.
+- Part one: support scale subresource api for workspace, so different auto-scaler solutions such as KEDA, HPA, etc. can be integrated with KAITO to mamage inference workloads dynamically. This part is addressed in this proposal.
 - Part two: support a customized auto-sacler for kaito. The auto-scaler is designed for a minimalistic configuration experience, with most parameters pre-tuned for optimal performance. This allows users to easily get started without requiring specialized knowledge of LLM. This part will be addressed in another proposal.
 
 ## Motivation
 
-LLM inference service is a baisc and widly-used feature in Kaito, and Kaito community interest in auto scaler for inference workloads continues to intensify, related issues: [#306](https://github.com/kaito-project/kaito/issues/306), [#1104](https://github.com/kaito-project/kaito/issues/1104).
+LLM inference service is a baisc and widly-used feature in KAITO, and KAITO community interest in auto scaler for inference workloads continues to intensify, related issues: [#306](https://github.com/kaito-project/kaito/issues/306), [#1104](https://github.com/kaito-project/kaito/issues/1104).
 
 From the technical perspective, It's a good idea to provide auto-scaler capability, becasue the auto-scaler of inference workloads dynamically adjusts the number of inference instances based on request volume--scaling up during traffic spikes to improve inference speed, and scaling down during low demand to minimize GPU resource waste.
 
-To ensure different auto-scaler solutions can integrate with Kaito to manage inference workloads dynamically, We aim to support scale subresource API for Workspace CRD in kaito.
+To ensure different auto-scaler solutions can integrate with KAITO to manage inference workloads dynamically, We aim to support scale subresource API for Workspace CRD in KAITO.
 
 ### Goals
 
diff --git a/docs/proposals/20250630-kaito-cli.md b/docs/proposals/20250630-kaito-cli.md
index 365e784..5bfa9cb 100644
--- a/docs/proposals/20250630-kaito-cli.md
+++ b/docs/proposals/20250630-kaito-cli.md
@@ -1,5 +1,5 @@
 ---
-title: Kaito Kubectl CLI Plugin
+title: KAITO Kubectl CLI Plugin
 authors:
   - "@helayoty"
 creation-date: 2025-06-30
@@ -10,7 +10,7 @@ see-also:
 
 ## Summary
 
-Kaito CLI provides a user-friendly kubectl extension for deploying and managing KAITO workspaces on Kubernetes. Kaito kubectl plugin aims to reduce friction for data scientists and ML engineers by abstracting away error-prone YAML authoring and enabling streamlined model deployment workflows. The initial focus is on core deployment and inference scenarios, with potential expansion to a standalone CLI if advanced features beyond kubectl's scope are needed.
+KAITO CLI provides a user-friendly kubectl extension for deploying and managing KAITO workspaces on Kubernetes. KAITO kubectl plugin aims to reduce friction for data scientists and ML engineers by abstracting away error-prone YAML authoring and enabling streamlined model deployment workflows. The initial focus is on core deployment and inference scenarios, with potential expansion to a standalone CLI if advanced features beyond kubectl's scope are needed.
 
 ## Motivation
 
@@ -40,7 +40,7 @@ Currently, users interact with KAITO by manually crafting Kubernetes YAML manife
 
 ### Kubectl Plugin
 
-A new kubectl plugin distributed through [Krew](https://github.com/kubernetes-sigs/krew) for Kaito that provides seamless integration with existing Kubernetes workflows.
+A new kubectl plugin distributed through [Krew](https://github.com/kubernetes-sigs/krew) for KAITO that provides seamless integration with existing Kubernetes workflows.
 
 Designed for engineers already comfortable with native Kubernetes tooling. By distributing the plugin through [Krew](https://github.com/kubernetes-sigs/krew), users avoid installing a separate binary, inherit their existing kube-contexts and RBAC, and benefit from familiar `kubectl` verb–noun syntax.
 
diff --git a/examples/custom-model-integration/Dockerfile.reference b/examples/custom-model-integration/Dockerfile.reference
index 2673482..3eb01ae 100644
--- a/examples/custom-model-integration/Dockerfile.reference
+++ b/examples/custom-model-integration/Dockerfile.reference
@@ -1,6 +1,6 @@
 FROM python:3.12-slim
 
-# Specify the repository source URL for reference and access in Kaito packages.
+# Specify the repository source URL for reference and access in KAITO packages.
 LABEL org.opencontainers.image.source=https://github.com/kaito-project/kaito
 
 ARG MODEL_TYPE
diff --git a/examples/custom-model-integration/reference-image-deployment.yaml b/examples/custom-model-integration/reference-image-deployment.yaml
index 2d81557..fc85c77 100644
--- a/examples/custom-model-integration/reference-image-deployment.yaml
+++ b/examples/custom-model-integration/reference-image-deployment.yaml
@@ -14,7 +14,7 @@ inference:
     spec:
       containers:
         - name: custom-llm-container
-          image: ghcr.io/kaito-project/kaito/llm-reference-preset:latest # Kaito Reference Image
+          image: ghcr.io/kaito-project/kaito/llm-reference-preset:latest # KAITO Reference Image
           livenessProbe:
             failureThreshold: 3
             httpGet:
diff --git a/pkg/featuregates/featuregates.go b/pkg/featuregates/featuregates.go
index 1ae194c..e6d04c2 100644
--- a/pkg/featuregates/featuregates.go
+++ b/pkg/featuregates/featuregates.go
@@ -23,7 +23,7 @@ import (
 )
 
 var (
-	// FeatureGates is a map that holds the feature gate names and their default values for Kaito.
+	// FeatureGates is a map that holds the feature gate names and their default values for KAITO.
 	FeatureGates = map[string]bool{
 		consts.FeatureFlagVLLM:                         true,
 		consts.FeatureFlagEnsureNodeClass:              false,
diff --git a/pkg/model/interface.go b/pkg/model/interface.go
index 2f2aecf..66272d4 100644
--- a/pkg/model/interface.go
+++ b/pkg/model/interface.go
@@ -82,13 +82,13 @@ type Metadata struct {
 	// DownloadAtRuntime indicates whether the model should be downloaded
 	// at runtime. If set to true, the model will be downloaded when the
 	// model deployment is created, and the container image will always be
-	// the Kaito base image. If set to false, a container image whose name
+	// the KAITO base image. If set to false, a container image whose name
 	// contains the model name will be used, in which the model weights are baked.
 	// +optional
 	DownloadAtRuntime bool `yaml:"downloadAtRuntime,omitempty"`
 
 	// Tag is the tag of the container image used to run the model.
-	// If the model uses the Kaito base image, the tag field can be ignored
+	// If the model uses the KAITO base image, the tag field can be ignored
 	// +optional
 	Tag string `yaml:"tag,omitempty"`
 
diff --git a/pkg/utils/plugin/plugin.go b/pkg/utils/plugin/plugin.go
index f112f2d..2801908 100644
--- a/pkg/utils/plugin/plugin.go
+++ b/pkg/utils/plugin/plugin.go
@@ -21,7 +21,7 @@ import (
 
 // Registration is a struct that holds the name and an instance of a struct
 // that implements the model.Model interface. It is used to register and manage
-// different model instances within the Kaito framework.
+// different model instances within the KAITO framework.
 type Registration struct {
 	// Name is the name of the model. It is used as a key to register and
 	// retrieve the model metadata and instance.
diff --git a/website/docs/usage.md b/website/docs/usage.md
index 8df434a..8fada1e 100644
--- a/website/docs/usage.md
+++ b/website/docs/usage.md
@@ -2,8 +2,8 @@
 title: Usage
 ---
 
-The detailed usage for Kaito supported models can be found in [**HERE**](./presets.md). In case users want to deploy their own containerized models, they can provide the pod template in the `inference` field of the workspace custom resource (please see [API definitions](../../api/v1alpha1/workspace_types.go) for details). The controller will create a deployment workload using all provisioned GPU nodes. Note that currently the controller does **NOT** handle automatic model upgrade. It only creates inference workloads based on the preset configurations if the workloads do not exist.
+The detailed usage for KAITO supported models can be found in [**HERE**](./presets.md). In case users want to deploy their own containerized models, they can provide the pod template in the `inference` field of the workspace custom resource (please see [API definitions](../../api/v1alpha1/workspace_types.go) for details). The controller will create a deployment workload using all provisioned GPU nodes. Note that currently the controller does **NOT** handle automatic model upgrade. It only creates inference workloads based on the preset configurations if the workloads do not exist.
 
-The number of the supported models in Kaito is growing! Please check [this](./preset-onboarding.md) document to see how to add a new supported model.
+The number of the supported models in KAITO is growing! Please check [this](./preset-onboarding.md) document to see how to add a new supported model.
 
-Starting with version v0.3.0, Kaito supports model fine-tuning and using fine-tuned adapters in the inference service. Refer to the [tuning document](./tuning.md) and [inference document](./inference.md) for more information.
+Starting with version v0.3.0, KAITO supports model fine-tuning and using fine-tuned adapters in the inference service. Refer to the [tuning document](./tuning.md) and [inference document](./inference.md) for more information.



Test patch:
diff --git a/test/e2e/inference_with_adapters_test.go b/test/e2e/inference_with_adapters_test.go
index 3d09bb9..bab492f 100644
--- a/test/e2e/inference_with_adapters_test.go
+++ b/test/e2e/inference_with_adapters_test.go
@@ -231,7 +231,7 @@ var _ = Describe("Workspace Preset", func() {
 	AfterEach(func() {
 		if CurrentSpecReport().Failed() {
 			utils.PrintPodLogsOnFailure(namespaceName, "")     // The Preset Pod
-			utils.PrintPodLogsOnFailure("kaito-workspace", "") // The Kaito Workspace Pod
+			utils.PrintPodLogsOnFailure("kaito-workspace", "") // The KAITO Workspace Pod
 			if !*skipGPUProvisionerCheck {
 				utils.PrintPodLogsOnFailure("gpu-provisioner", "") // The gpu-provisioner Pod
 			}
diff --git a/test/e2e/preset_test.go b/test/e2e/preset_test.go
index 039b117..9a832a0 100644
--- a/test/e2e/preset_test.go
+++ b/test/e2e/preset_test.go
@@ -1081,7 +1081,7 @@ var _ = Describe("Workspace Preset", func() {
 	AfterEach(func() {
 		if CurrentSpecReport().Failed() {
 			utils.PrintPodLogsOnFailure(namespaceName, "")     // The Preset Pod
-			utils.PrintPodLogsOnFailure("kaito-workspace", "") // The Kaito Workspace Pod
+			utils.PrintPodLogsOnFailure("kaito-workspace", "") // The KAITO Workspace Pod
 			if !*skipGPUProvisionerCheck {
 				utils.PrintPodLogsOnFailure("gpu-provisioner", "") // The gpu-provisioner Pod
 			}
diff --git a/test/e2e/preset_vllm_test.go b/test/e2e/preset_vllm_test.go
index 436d31c..8fa0374 100644
--- a/test/e2e/preset_vllm_test.go
+++ b/test/e2e/preset_vllm_test.go
@@ -41,7 +41,7 @@ var _ = Describe("Workspace Preset on vllm runtime", func() {
 	AfterEach(func() {
 		if CurrentSpecReport().Failed() {
 			utils.PrintPodLogsOnFailure(namespaceName, "")     // The Preset Pod
-			utils.PrintPodLogsOnFailure("kaito-workspace", "") // The Kaito Workspace Pod
+			utils.PrintPodLogsOnFailure("kaito-workspace", "") // The KAITO Workspace Pod
 			if !*skipGPUProvisionerCheck {
 				utils.PrintPodLogsOnFailure("gpu-provisioner", "") // The gpu-provisioner Pod
 			}
diff --git a/test/rage2e/rag_test.go b/test/rage2e/rag_test.go
index 6e4cd3a..1f467fa 100644
--- a/test/rage2e/rag_test.go
+++ b/test/rage2e/rag_test.go
@@ -81,8 +81,8 @@ var _ = Describe("RAGEngine", func() {
 	AfterEach(func() {
 		if CurrentSpecReport().Failed() {
 			utils.PrintPodLogsOnFailure(namespaceName, "")     // The Preset Pod
-			utils.PrintPodLogsOnFailure("kaito-workspace", "") // The Kaito Workspace Pod
-			utils.PrintPodLogsOnFailure("kaito-ragengine", "") // The Kaito ragengine Pod
+			utils.PrintPodLogsOnFailure("kaito-workspace", "") // The KAITO Workspace Pod
+			utils.PrintPodLogsOnFailure("kaito-ragengine", "") // The KAITO ragengine Pod
 			if !*skipGPUProvisionerCheck {
 				utils.PrintPodLogsOnFailure("gpu-provisioner", "") // The gpu-provisioner Pod
 			}
@@ -110,7 +110,7 @@ var _ = Describe("RAGEngine", func() {
 		Expect(indexDoc["text"]).NotTo(BeNil(), "Index document text should not be nil")
 		docID := indexDoc["doc_id"].(string)
 
-		searchQuerySuccess := "Kaito is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster"
+		searchQuerySuccess := "KAITO is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster"
 		err = createAndValidateQueryPod(ragengineObj, searchQuerySuccess, true)
 		Expect(err).NotTo(HaveOccurred(), "Failed to create and validate QueryPod")
 
@@ -176,7 +176,7 @@ var _ = Describe("RAGEngine", func() {
 		Expect(indexDoc["text"]).NotTo(BeNil(), "Index document text should not be nil")
 		docID := indexDoc["doc_id"].(string)
 
-		searchQuerySuccess := "Kaito is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster"
+		searchQuerySuccess := "KAITO is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster"
 		err = createAndValidateQueryPod(ragengineObj, searchQuerySuccess, false)
 		Expect(err).NotTo(HaveOccurred(), "Failed to create and validate QueryPod")
 
@@ -243,7 +243,7 @@ var _ = Describe("RAGEngine", func() {
 		Expect(indexDoc["text"]).NotTo(BeNil(), "Index document text should not be nil")
 		docID := indexDoc["doc_id"].(string)
 
-		searchQuerySuccess := "Kaito is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster"
+		searchQuerySuccess := "KAITO is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster"
 		err = createAndValidateQueryPod(ragengineObj, searchQuerySuccess, false)
 		Expect(err).NotTo(HaveOccurred(), "Failed to create and validate QueryPod")
 
@@ -306,11 +306,11 @@ var _ = Describe("RAGEngine", func() {
 		Expect(indexDoc["text"]).NotTo(BeNil(), "Index document text should not be nil")
 		docID := indexDoc["doc_id"].(string)
 
-		searchQuerySuccess := "Kaito is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster"
+		searchQuerySuccess := "KAITO is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster"
 		err = createAndValidateQueryChatMessagesPod(ragengineObj, searchQuerySuccess, false)
 		Expect(err).NotTo(HaveOccurred(), "Failed to create and validate QueryChatMessagesPod")
 
-		persistLogSuccess := "Successfully persisted index kaito"
+		persistLogSuccess := "Successfully persisted index KAITO"
 		err = createAndValidatePersistPod(ragengineObj, persistLogSuccess)
 		Expect(err).NotTo(HaveOccurred(), "Failed to create and validate PersistPod")
 
@@ -736,7 +736,7 @@ func createAndValidateIndexPod(ragengineObj *kaitov1alpha1.RAGEngine) (map[strin
     "index_name": "kaito",
     "documents": [
         {
-            "text": "Kaito is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster",
+            "text": "KAITO is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster",
             "metadata": {"author": "kaito", "category": "kaito"}
         }
     ]
@@ -745,7 +745,7 @@ func createAndValidateIndexPod(ragengineObj *kaitov1alpha1.RAGEngine) (map[strin
 		PodName:            fmt.Sprintf("index-pod-%s", utils.GenerateRandomString()),
 		CurlCommand:        curlCommand,
 		Namespace:          ragengineObj.ObjectMeta.Namespace,
-		ExpectedLogContent: "Kaito is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster",
+		ExpectedLogContent: "KAITO is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster",
 		WaitForRunning:     false,
 		ParseJSONResponse:  true,
 		JSONStartMarker:    "[",
@@ -761,7 +761,7 @@ func createAndValidateUpdateDocumentPod(ragengineObj *kaitov1alpha1.RAGEngine, d
     "documents": [
         {
 			"doc_id": "` + docID + `",
-            "text": "Kaito is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster. It now has RAG capabilities.",
+            "text": "KAITO is an operator that automates the AI/ML model inference or tuning workload in a Kubernetes cluster. It now has RAG capabilities.",
             "metadata": {"author": "kaito", "category": "ai-ml"}
         }
     ]