diff --git a/CHANGELOG.md b/CHANGELOG.md
index 2cfc9ca9..7e7003a8 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -7,6 +7,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+- Added support for Amazon Nova models (amazon.nova-micro-v1:0, amazon.nova-lite-v1:0, amazon.nova-pro-v1:0)
+- Updated Anthropic Claude models to the latest 3.5 versions (anthropic.claude-3-5-haiku-20241022-v1:0, anthropic.claude-3-5-sonnet-20241022-v2:0)
+- Removed older versions of Amazon Titan and Anthropic Claude models (amazon.titan-text-express-v1, anthropic.claude-v1, anthropic.claude-instant-v1, anthropic.claude-v2)
+- Refactored Bedrock calls to use the Converse API eliminating the need for custom model specific payloads
+- Refactored all model invocation to use Inference Profiles. This is required for Nova models. It is also applied to Anthropic models for consistency and improved scalability.
+- Added adaptive retry configuration to Bedrock api calls to add some tolerance for quota throttling exceptions (at the expense of latency)
+
 ## [0.7.11] - 2024-10-09
 
 ### Added
diff --git a/pca-main-nokendra.template b/pca-main-nokendra.template
index 9a6e808d..93c52758 100644
--- a/pca-main-nokendra.template
+++ b/pca-main-nokendra.template
@@ -384,14 +384,17 @@ Parameters:
 
   GenAIQueryBedrockModelId:
     Type: String
-    Default: anthropic.claude-3-haiku-20240307-v1:0
+    Default: us.amazon.nova-lite-v1:0
     AllowedValues:
       - anthropic.claude-3-haiku-20240307-v1:0
       - anthropic.claude-3-sonnet-20240229-v1:0
-      - amazon.titan-text-express-v1
-      - anthropic.claude-v1
-      - anthropic.claude-instant-v1
-      - anthropic.claude-v2
+      - us.amazon.nova-micro-v1:0
+      - us.amazon.nova-lite-v1:0
+      - us.amazon.nova-pro-v1:0
+      - us.anthropic.claude-3-5-haiku-20241022-v1:0
+      - us.anthropic.claude-3-5-sonnet-20241022-v2:0
+      - eu.anthropic.claude-3-5-sonnet-20240620-v1:0
+      - apac.anthropic.claude-3-5-sonnet-20240620-v1:0
     Description: (Optional) If 'GenAIQuery' is BEDROCK, which Bedrock model to use.
 
   CallSummarization:
@@ -417,14 +420,17 @@ Parameters:
   
   SummarizationBedrockModelId:
     Type: String
-    Default: anthropic.claude-3-haiku-20240307-v1:0
+    Default: us.amazon.nova-lite-v1:0
     AllowedValues:
       - anthropic.claude-3-haiku-20240307-v1:0
       - anthropic.claude-3-sonnet-20240229-v1:0
-      - amazon.titan-text-express-v1
-      - anthropic.claude-v1
-      - anthropic.claude-instant-v1
-      - anthropic.claude-v2
+      - us.amazon.nova-micro-v1:0
+      - us.amazon.nova-lite-v1:0
+      - us.amazon.nova-pro-v1:0
+      - us.anthropic.claude-3-5-haiku-20241022-v1:0
+      - us.anthropic.claude-3-5-sonnet-20241022-v2:0
+      - eu.anthropic.claude-3-5-sonnet-20240620-v1:0
+      - apac.anthropic.claude-3-5-sonnet-20240620-v1:0
     Description: (Optional) If 'CallSummarization' is BEDROCK, which Bedrock model to use.
 
   TestBedrockModelId:
@@ -714,6 +720,12 @@ Resources:
                 Resource:
                   - !Sub "arn:${AWS::Partition}:bedrock:*::foundation-model/*"
                   - !Sub "arn:${AWS::Partition}:bedrock:*:${AWS::AccountId}:custom-model/*"
+                  - !Sub "arn:aws:bedrock:${AWS::Region}:${AWS::AccountId}:inference-profile/*"
+              - Effect: Allow
+                Action:
+                  - "bedrock:GetInferenceProfile"
+                Resource:
+                  - !Sub "arn:aws:bedrock:${AWS::Region}:${AWS::AccountId}:inference-profile/*"
           PolicyName: BedrockPolicy
 
   TestBedrockModelFunction:
@@ -736,76 +748,38 @@ Resources:
           subprocess.check_call([sys.executable, '-m', 'pip', 'install', '--target', '/tmp', 'boto3'])
           sys.path.insert(0,'/tmp')
           import boto3
-
+          from botocore.config import Config
+          
           # Defaults
           AWS_REGION = os.environ["AWS_REGION_OVERRIDE"] if "AWS_REGION_OVERRIDE" in os.environ else os.environ["AWS_REGION"]
           ENDPOINT_URL = os.environ.get("ENDPOINT_URL", f'https://bedrock-runtime.{AWS_REGION}.amazonaws.com')
           DEFAULT_MAX_TOKENS = 128
 
-          def get_request_body(modelId, parameters, prompt):
-              provider = modelId.split(".")[0]
-              request_body = None
-              if provider == "anthropic":
-                  if 'claude-3' in modelId:
-                      request_body = {
-                          "max_tokens": DEFAULT_MAX_TOKENS,
-                          "messages": [{"role": "user", "content": prompt}],
-                          "anthropic_version": "bedrock-2023-05-31"
-                      }
-                  else:    
-                      request_body = {
-                          "prompt": prompt,
-                          "max_tokens_to_sample": DEFAULT_MAX_TOKENS
-                      } 
-
-                  request_body.update(parameters)
-              elif provider == "ai21":
-                  request_body = {
-                      "prompt": prompt,
-                      "maxTokens": DEFAULT_MAX_TOKENS
+          def get_generate_text(response):
+            return response["output"]["message"]["content"][0]["text"]
+
+          def call_llm(prompt, modelId):
+              client = boto3.client(
+                service_name='bedrock-runtime', 
+                region_name=AWS_REGION, 
+                endpoint_url=ENDPOINT_URL, 
+                config=Config(retries={'max_attempts': 50, 'mode': 'adaptive'})
+              )
+              
+              message = {
+                  'role': 'user',
+                  'content': [{'text': prompt}]
+              }
+
+              response = client.converse(
+                  modelId=modelId,
+                  messages=[message],
+                  inferenceConfig={
+                      'maxTokens': DEFAULT_MAX_TOKENS,
+                      'temperature': 0
                   }
-                  request_body.update(parameters)
-              elif provider == "amazon":
-                  textGenerationConfig = {
-                      "maxTokenCount": DEFAULT_MAX_TOKENS
-                  }
-                  textGenerationConfig.update(parameters)
-                  request_body = {
-                      "inputText": prompt,
-                      "textGenerationConfig": textGenerationConfig
-                  }
-              else:
-                  raise Exception("Unsupported provider: ", provider)
-              return request_body
-
-          def get_generate_text(modelId, response):
-              provider = modelId.split(".")[0]
-              generated_text = None
-              if provider == "anthropic":
-                  if 'claude-3' in modelId:
-                      response_raw = json.loads(response.get("body").read().decode())
-                      generated_text = response_raw.get('content')[0].get('text')
-          
-                  else:
-                      response_body = json.loads(response.get("body").read().decode())
-                      generated_text = response_body.get("completion")
-              elif provider == "ai21":
-                  response_body = json.loads(response.get("body").read())
-                  generated_text = response_body.get("completions")[0].get("data").get("text")
-              elif provider == "amazon":
-                  response_body = json.loads(response.get("body").read())
-                  generated_text = response_body.get("results")[0].get("outputText")
-              else:
-                  raise Exception("Unsupported provider: ", provider)
-              return generated_text
-
-          def call_llm(parameters, prompt):
-              modelId = parameters.pop("modelId")
-              body = get_request_body(modelId, parameters, prompt)
-              print("ModelId", modelId, "-  Body: ", body)
-              client = boto3.client(service_name='bedrock-runtime', region_name=AWS_REGION, endpoint_url=ENDPOINT_URL)
-              response = client.invoke_model(body=json.dumps(body), modelId=modelId, accept='application/json', contentType='application/json')
-              generated_text = get_generate_text(modelId, response)
+              )
+              generated_text = get_generate_text(response)
               return generated_text
 
           def lambda_handler(event, context):
@@ -821,12 +795,8 @@ Resources:
                       # Test LLMModel
                       llmModelId = event['ResourceProperties'].get('LLMModelId', '')
                       modelId = llmModelId
-                      parameters = {
-                          "modelId": modelId,
-                          "temperature": 0
-                      }
                       print(f"Testing {modelId}")
-                      call_llm(parameters, prompt)            
+                      call_llm(prompt, modelId)               
                   except Exception as e:
                       status = cfnresponse.FAILED
                       reason = f"Exception thrown testing ModelId='{modelId}'. Check that Amazon Bedrock is available in your region, and that model is activated in your Amazon Bedrock account - {e}"
diff --git a/pca-main.template b/pca-main.template
index 428e65af..05b2bb4b 100644
--- a/pca-main.template
+++ b/pca-main.template
@@ -425,14 +425,17 @@ Parameters:
 
   GenAIQueryBedrockModelId:
     Type: String
-    Default: anthropic.claude-3-haiku-20240307-v1:0
+    Default: us.amazon.nova-lite-v1:0
     AllowedValues:
       - anthropic.claude-3-haiku-20240307-v1:0
       - anthropic.claude-3-sonnet-20240229-v1:0
-      - amazon.titan-text-express-v1
-      - anthropic.claude-v1
-      - anthropic.claude-instant-v1
-      - anthropic.claude-v2
+      - us.amazon.nova-micro-v1:0
+      - us.amazon.nova-lite-v1:0
+      - us.amazon.nova-pro-v1:0
+      - us.anthropic.claude-3-5-haiku-20241022-v1:0
+      - us.anthropic.claude-3-5-sonnet-20241022-v2:0
+      - eu.anthropic.claude-3-5-sonnet-20240620-v1:0
+      - apac.anthropic.claude-3-5-sonnet-20240620-v1:0
     Description: (Optional) If 'GenAIQuery' is BEDROCK, which Bedrock model to use.
 
   CallSummarization:
@@ -458,14 +461,17 @@ Parameters:
 
   SummarizationBedrockModelId:
     Type: String
-    Default: anthropic.claude-3-haiku-20240307-v1:0
+    Default: us.amazon.nova-lite-v1:0
     AllowedValues:
       - anthropic.claude-3-haiku-20240307-v1:0
       - anthropic.claude-3-sonnet-20240229-v1:0
-      - amazon.titan-text-express-v1
-      - anthropic.claude-v1
-      - anthropic.claude-instant-v1
-      - anthropic.claude-v2
+      - us.amazon.nova-micro-v1:0
+      - us.amazon.nova-lite-v1:0
+      - us.amazon.nova-pro-v1:0
+      - us.anthropic.claude-3-5-haiku-20241022-v1:0
+      - us.anthropic.claude-3-5-sonnet-20241022-v2:0
+      - eu.anthropic.claude-3-5-sonnet-20240620-v1:0
+      - apac.anthropic.claude-3-5-sonnet-20240620-v1:0
     Description: (Optional) If 'CallSummarization' is BEDROCK, which Bedrock model to use. 
 
   TestBedrockModelId:
@@ -897,6 +903,12 @@ Resources:
                 Resource:
                   - !Sub "arn:${AWS::Partition}:bedrock:*::foundation-model/*"
                   - !Sub "arn:${AWS::Partition}:bedrock:*:${AWS::AccountId}:custom-model/*"
+                  - !Sub "arn:aws:bedrock:${AWS::Region}:${AWS::AccountId}:inference-profile/*"
+              - Effect: Allow
+                Action:
+                  - "bedrock:GetInferenceProfile"
+                Resource:
+                  - !Sub "arn:aws:bedrock:${AWS::Region}:${AWS::AccountId}:inference-profile/*"
           PolicyName: BedrockPolicy
 
   TestBedrockModelFunction:
@@ -919,76 +931,38 @@ Resources:
           subprocess.check_call([sys.executable, '-m', 'pip', 'install', '--target', '/tmp', 'boto3'])
           sys.path.insert(0,'/tmp')
           import boto3
-
+          from botocore.config import Config
+          
           # Defaults
           AWS_REGION = os.environ["AWS_REGION_OVERRIDE"] if "AWS_REGION_OVERRIDE" in os.environ else os.environ["AWS_REGION"]
           ENDPOINT_URL = os.environ.get("ENDPOINT_URL", f'https://bedrock-runtime.{AWS_REGION}.amazonaws.com')
           DEFAULT_MAX_TOKENS = 128
 
-          def get_request_body(modelId, parameters, prompt):
-              provider = modelId.split(".")[0]
-              request_body = None
-              if provider == "anthropic":
-                  if 'claude-3' in modelId:
-                      request_body = {
-                          "max_tokens": DEFAULT_MAX_TOKENS,
-                          "messages": [{"role": "user", "content": prompt}],
-                          "anthropic_version": "bedrock-2023-05-31"
-                      }
-                  else:    
-                      request_body = {
-                          "prompt": prompt,
-                          "max_tokens_to_sample": DEFAULT_MAX_TOKENS
-                      } 
-
-                  request_body.update(parameters)
-              elif provider == "ai21":
-                  request_body = {
-                      "prompt": prompt,
-                      "maxTokens": DEFAULT_MAX_TOKENS
-                  }
-                  request_body.update(parameters)
-              elif provider == "amazon":
-                  textGenerationConfig = {
-                      "maxTokenCount": DEFAULT_MAX_TOKENS
+          def get_generate_text(response):
+            return response["output"]["message"]["content"][0]["text"]
+
+          def call_llm(prompt, modelId):
+              client = boto3.client(
+                service_name='bedrock-runtime', 
+                region_name=AWS_REGION, 
+                endpoint_url=ENDPOINT_URL, 
+                config=Config(retries={'max_attempts': 50, 'mode': 'adaptive'})
+              )
+              
+              message = {
+                  'role': 'user',
+                  'content': [{'text': prompt}]
+              }
+
+              response = client.converse(
+                  modelId=modelId,
+                  messages=[message],
+                  inferenceConfig={
+                      'maxTokens': DEFAULT_MAX_TOKENS,
+                      'temperature': 0
                   }
-                  textGenerationConfig.update(parameters)
-                  request_body = {
-                      "inputText": prompt,
-                      "textGenerationConfig": textGenerationConfig
-                  }
-              else:
-                  raise Exception("Unsupported provider: ", provider)
-              return request_body
-
-          def get_generate_text(modelId, response):
-              provider = modelId.split(".")[0]
-              generated_text = None
-              if provider == "anthropic":
-                  if 'claude-3' in modelId:
-                      response_raw = json.loads(response.get("body").read().decode())
-                      generated_text = response_raw.get('content')[0].get('text')
-          
-                  else:
-                      response_body = json.loads(response.get("body").read().decode())
-                      generated_text = response_body.get("completion")
-              elif provider == "ai21":
-                  response_body = json.loads(response.get("body").read())
-                  generated_text = response_body.get("completions")[0].get("data").get("text")
-              elif provider == "amazon":
-                  response_body = json.loads(response.get("body").read())
-                  generated_text = response_body.get("results")[0].get("outputText")
-              else:
-                  raise Exception("Unsupported provider: ", provider)
-              return generated_text
-
-          def call_llm(parameters, prompt):
-              modelId = parameters.pop("modelId")
-              body = get_request_body(modelId, parameters, prompt)
-              print("ModelId", modelId, "-  Body: ", body)
-              client = boto3.client(service_name='bedrock-runtime', region_name=AWS_REGION, endpoint_url=ENDPOINT_URL)
-              response = client.invoke_model(body=json.dumps(body), modelId=modelId, accept='application/json', contentType='application/json')
-              generated_text = get_generate_text(modelId, response)
+              )
+              generated_text = get_generate_text(response)
               return generated_text
 
           def lambda_handler(event, context):
@@ -1004,12 +978,9 @@ Resources:
                       # Test LLMModel
                       llmModelId = event['ResourceProperties'].get('LLMModelId', '')
                       modelId = llmModelId
-                      parameters = {
-                          "modelId": modelId,
-                          "temperature": 0
-                      }
+
                       print(f"Testing {modelId}")
-                      call_llm(parameters, prompt)            
+                      call_llm(prompt, modelId)            
                   except Exception as e:
                       status = cfnresponse.FAILED
                       reason = f"Exception thrown testing ModelId='{modelId}'. Check that Amazon Bedrock is available in your region, and that model is activated in your Amazon Bedrock account - {e}"
diff --git a/pca-server/cfn/lib/pca.template b/pca-server/cfn/lib/pca.template
index 37a21559..9e4075fa 100644
--- a/pca-server/cfn/lib/pca.template
+++ b/pca-server/cfn/lib/pca.template
@@ -322,6 +322,13 @@ Resources:
               Resource:
                 - !Sub arn:${AWS::Partition}:bedrock:*::foundation-model/*
                 - !Sub arn:${AWS::Partition}:bedrock:*:${AWS::AccountId}:custom-model/*
+                - !Sub arn:aws:bedrock:${AWS::Region}:${AWS::AccountId}:inference-profile/*
+            - Sid: BedrockGetInferenceProfile
+              Effect: Allow
+              Action:
+                - bedrock:GetInferenceProfile
+              Resource:
+                - !Sub arn:aws:bedrock:${AWS::Region}:${AWS::AccountId}:inference-profile/*
             - !If
               - HasAnthropicSummary
               - Sid: SecretsManagerPolicy
diff --git a/pca-server/cfn/pca-server.template b/pca-server/cfn/pca-server.template
index d73a0869..2bf16292 100644
--- a/pca-server/cfn/pca-server.template
+++ b/pca-server/cfn/pca-server.template
@@ -40,14 +40,17 @@ Parameters:
   
   SummarizationBedrockModelId:
     Type: String
-    Default: anthropic.claude-3-haiku-20240307-v1:0
+    Default: us.amazon.nova-lite-v1:0
     AllowedValues:
       - anthropic.claude-3-haiku-20240307-v1:0
       - anthropic.claude-3-sonnet-20240229-v1:0
-      - amazon.titan-text-express-v1
-      - anthropic.claude-v1
-      - anthropic.claude-instant-v1
-      - anthropic.claude-v2
+      - us.amazon.nova-micro-v1:0
+      - us.amazon.nova-lite-v1:0
+      - us.amazon.nova-pro-v1:0
+      - us.anthropic.claude-3-5-haiku-20241022-v1:0
+      - us.anthropic.claude-3-5-sonnet-20241022-v2:0
+      - eu.anthropic.claude-3-5-sonnet-20240620-v1:0
+      - apac.anthropic.claude-3-5-sonnet-20240620-v1:0
     Description: (Optional) If 'CallSummarization' is BEDROCK, which Bedrock model to use.
 
   SummarizationSageMakerInitialInstanceCount:
diff --git a/pca-server/src/pca/pca-aws-sf-summarize.py b/pca-server/src/pca/pca-aws-sf-summarize.py
index a66d6c8c..92081df2 100644
--- a/pca-server/src/pca/pca-aws-sf-summarize.py
+++ b/pca-server/src/pca/pca-aws-sf-summarize.py
@@ -35,13 +35,6 @@
 s3Client = boto3.client('s3')
 dynamodb_client = boto3.client('dynamodb')
 
-config = Config(
-   retries = {
-      'max_attempts': 100,
-      'mode': 'adaptive'
-   }
-)
-
 def get_third_party_llm_secret():
     print("Getting API key from Secrets Manager")
     secrets_client = boto3.client('secretsmanager')
@@ -56,76 +49,43 @@ def get_third_party_llm_secret():
 
 def get_bedrock_client():
     print("Connecting to Bedrock Service: ", BEDROCK_ENDPOINT_URL)
-    client = boto3.client(service_name='bedrock-runtime', region_name=AWS_REGION, endpoint_url=BEDROCK_ENDPOINT_URL, config=config)
+    client = boto3.client(
+        service_name='bedrock-runtime', 
+        region_name=AWS_REGION, 
+        endpoint_url=BEDROCK_ENDPOINT_URL,
+        config=Config(retries={'max_attempts': 50, 'mode': 'adaptive'})
+    )
     return client
-    
-def get_bedrock_request_body(modelId, parameters, prompt):
-    provider = modelId.split(".")[0]
-    request_body = None
-    if provider == "anthropic":
-        if 'claude-3' in modelId:
-            request_body = {
-                "max_tokens": MAX_TOKENS,
-                "messages": [{"role": "user", "content": prompt}],
-                "anthropic_version": "bedrock-2023-05-31"
-            }
-        else:    
-            request_body = {
-                "prompt": prompt,
-                "max_tokens_to_sample": MAX_TOKENS
-            } 
-        request_body.update(parameters)
-    elif provider == "ai21":
-        request_body = {
-            "prompt": prompt,
-            "maxTokens": MAX_TOKENS
-        }
-        request_body.update(parameters)
-    elif provider == "amazon":
-        textGenerationConfig = {
-            "maxTokenCount": MAX_TOKENS
-        }
-        textGenerationConfig.update(parameters)
-        request_body = {
-            "inputText": prompt,
-            "textGenerationConfig": textGenerationConfig
-        }
-    else:
-        raise Exception("Unsupported provider: ", provider)
-    return request_body
-
-def get_bedrock_generate_text(modelId, response):
-    print("generating response with ", modelId)
-    provider = modelId.split(".")[0]
-    generated_text = None
-    if provider == "anthropic":
-        if 'claude-3' in modelId:
-            response_raw = json.loads(response.get("body").read().decode())
-            generated_text = response_raw.get('content')[0].get('text')
-
-        else:
-            response_body = json.loads(response.get("body").read().decode())
-            generated_text = response_body.get("completion")
-    elif provider == "ai21":
-        response_body = json.loads(response.get("body").read())
-        generated_text = response_body.get("completions")[0].get("data").get("text")
-    elif provider == "amazon":
-        response_body = json.loads(response.get("body").read())
-        generated_text = response_body.get("results")[0].get("outputText")
-    else:
-        raise Exception("Unsupported provider: ", provider)
+
+def get_bedrock_generate_text(response):
+    generated_text = response["output"]["message"]["content"][0]["text"]
     generated_text = generated_text.replace('```','')
     return generated_text
 
-def call_bedrock(parameters, prompt):
+def call_bedrock(prompt, temperature, max_tokens):
     global bedrock_client
     modelId = BEDROCK_MODEL_ID
-    body = get_bedrock_request_body(modelId, parameters, prompt)
-    print("ModelId", modelId, "-  Body: ", body)
+
+    print(f"Bedrock request - ModelId: {modelId} Temperature: {temperature} Max Tokens: {max_tokens}")
+    
     if (bedrock_client is None):
         bedrock_client = get_bedrock_client()
-    response = bedrock_client.invoke_model(body=json.dumps(body), modelId=modelId, accept='application/json', contentType='application/json')
-    generated_text = get_bedrock_generate_text(modelId, response)
+
+    message = {
+        "role": "user",
+        "content": [{"text": prompt}]
+    }
+
+    response = bedrock_client.converse(
+        modelId=modelId,
+        messages=[message],
+        inferenceConfig={
+            "maxTokens": max_tokens,
+            "temperature": temperature
+        }
+    )
+    
+    generated_text = get_bedrock_generate_text(response)
     return generated_text
 
 def generate_sagemaker_summary(transcript):
@@ -224,10 +184,7 @@ def generate_bedrock_summary(transcript, api_mode):
             continue
         else: 
             prompt = prompt.replace("{transcript}", transcript)
-            parameters = {
-                "temperature": 0
-            }
-            generated_text = call_bedrock(parameters, prompt)
+            generated_text = call_bedrock(prompt, 0, MAX_TOKENS)
             result[key] = generated_text
     if len(result.keys()) == 1:
         # This is a single node JSON with value that can be either:
diff --git a/pca-server/src/pca/pcaconfiguration.py b/pca-server/src/pca/pcaconfiguration.py
index 47134b2d..7b7b5cf8 100644
--- a/pca-server/src/pca/pcaconfiguration.py
+++ b/pca-server/src/pca/pcaconfiguration.py
@@ -7,54 +7,58 @@
 SPDX-License-Identifier: Apache-2.0
 """
 import boto3
+import os
 from botocore.config import Config
 
+# Get the stack name from environment variable
+STACK_NAME = os.environ.get('STACK_NAME')
+
 # Parameter Store Field Names used by main workflow
-CONF_COMP_LANGS = "ComprehendLanguages"
-CONF_REDACTION_LANGS = "ContentRedactionLanguages"
-CONF_CONVO_LOCATION = "ConversationLocation"
-CONF_ENTITYENDPOINT = "EntityRecognizerEndpoint"
-CONF_ENTITY_FILE = "EntityStringMap"
-CONF_ENTITYCONF = "EntityThreshold"
-CONF_ENTITY_TYPES = "EntityTypes"
-CONF_PREFIX_AUDIO_PLAYBACK = "InputBucketAudioPlayback"
-CONF_S3BUCKET_INPUT = "InputBucketName"
-CONF_PREFIX_RAW_AUDIO = "InputBucketRawAudio"
-CONF_PREFIX_FAILED_AUDIO = "InputBucketFailedTranscriptions"
-CONF_PREFIX_INPUT_TRANSCRIPTS = "InputBucketOrigTranscripts"
-CONF_MAX_SPEAKERS = "MaxSpeakers"
-CONF_MINNEGATIVE = "MinSentimentNegative"
-CONF_MINPOSITIVE = "MinSentimentPositive"
-CONF_S3BUCKET_OUTPUT = "OutputBucketName"
-CONF_PREFIX_TRANSCRIBE_RESULTS = "OutputBucketTranscribeResults"
-CONF_PREFIX_PARSED_RESULTS = "OutputBucketParsedResults"
-CONF_SPEAKER_NAMES = "SpeakerNames"
-CONF_SPEAKER_MODE = "SpeakerSeparationType"
-COMP_SFN_NAME = "StepFunctionName"
-CONF_SUPPORT_BUCKET = "SupportFilesBucketName"
-CONF_TRANSCRIBE_LANG = "TranscribeLanguages"
-CONF_TELEPHONY_CTR = "TelephonyCTRType"
-CONF_TELEPHONY_CTR_SUFFIX = "TelephonyCTRFileSuffix"
-CONF_VOCABNAME = "VocabularyName"
-CONF_CLMNAME = "CustomLangModelName"
-CONF_FILENAME_DATETIME_REGEX = "FilenameDatetimeRegex"
-CONF_FILENAME_DATETIME_FIELDMAP = "FilenameDatetimeFieldMap"
-CONF_FILENAME_GUID_REGEX = "FilenameGUIDRegex"
-CONF_FILENAME_AGENT_REGEX = "FilenameAgentRegex"
-CONF_FILENAME_CUST_REGEX = "FilenameCustRegex"
-CONF_FILTER_MODE = "VocabFilterMode"
-CONF_FILTER_NAME = "VocabFilterName"
-CONF_KENDRA_INDEX_ID = "KendraIndexId"
-CONF_WEB_URI = "WebUiUri"
-CONF_TRANSCRIBE_API = "TranscribeApiMode"
-CONF_REDACTION_TRANSCRIPT = "CallRedactionTranscript"
-CONF_REDACTION_AUDIO = "CallRedactionAudio"
-CONF_CALL_SUMMARIZATION = "CallSummarization"
+CONF_COMP_LANGS = f"{STACK_NAME}-ComprehendLanguages"
+CONF_REDACTION_LANGS = f"{STACK_NAME}-ContentRedactionLanguages"
+CONF_CONVO_LOCATION = f"{STACK_NAME}-ConversationLocation"
+CONF_ENTITYENDPOINT = f"{STACK_NAME}-EntityRecognizerEndpoint"
+CONF_ENTITY_FILE = f"{STACK_NAME}-EntityStringMap"
+CONF_ENTITYCONF = f"{STACK_NAME}-EntityThreshold"
+CONF_ENTITY_TYPES = f"{STACK_NAME}-EntityTypes"
+CONF_PREFIX_AUDIO_PLAYBACK = f"{STACK_NAME}-InputBucketAudioPlayback"
+CONF_S3BUCKET_INPUT = f"{STACK_NAME}-InputBucketName"
+CONF_PREFIX_RAW_AUDIO = f"{STACK_NAME}-InputBucketRawAudio"
+CONF_PREFIX_FAILED_AUDIO = f"{STACK_NAME}-InputBucketFailedTranscriptions"
+CONF_PREFIX_INPUT_TRANSCRIPTS = f"{STACK_NAME}-InputBucketOrigTranscripts"
+CONF_MAX_SPEAKERS = f"{STACK_NAME}-MaxSpeakers"
+CONF_MINNEGATIVE = f"{STACK_NAME}-MinSentimentNegative"
+CONF_MINPOSITIVE = f"{STACK_NAME}-MinSentimentPositive"
+CONF_S3BUCKET_OUTPUT = f"{STACK_NAME}-OutputBucketName"
+CONF_PREFIX_TRANSCRIBE_RESULTS = f"{STACK_NAME}-OutputBucketTranscribeResults"
+CONF_PREFIX_PARSED_RESULTS = f"{STACK_NAME}-OutputBucketParsedResults"
+CONF_SPEAKER_NAMES = f"{STACK_NAME}-SpeakerNames"
+CONF_SPEAKER_MODE = f"{STACK_NAME}-SpeakerSeparationType"
+COMP_SFN_NAME = f"{STACK_NAME}-StepFunctionName"
+CONF_SUPPORT_BUCKET = f"{STACK_NAME}-SupportFilesBucketName"
+CONF_TRANSCRIBE_LANG = f"{STACK_NAME}-TranscribeLanguages"
+CONF_TELEPHONY_CTR = f"{STACK_NAME}-TelephonyCTRType"
+CONF_TELEPHONY_CTR_SUFFIX = f"{STACK_NAME}-TelephonyCTRFileSuffix"
+CONF_VOCABNAME = f"{STACK_NAME}-VocabularyName"
+CONF_CLMNAME = f"{STACK_NAME}-CustomLangModelName"
+CONF_FILENAME_DATETIME_REGEX = f"{STACK_NAME}-FilenameDatetimeRegex"
+CONF_FILENAME_DATETIME_FIELDMAP = f"{STACK_NAME}-FilenameDatetimeFieldMap"
+CONF_FILENAME_GUID_REGEX = f"{STACK_NAME}-FilenameGUIDRegex"
+CONF_FILENAME_AGENT_REGEX = f"{STACK_NAME}-FilenameAgentRegex"
+CONF_FILENAME_CUST_REGEX = f"{STACK_NAME}-FilenameCustRegex"
+CONF_FILTER_MODE = f"{STACK_NAME}-VocabFilterMode"
+CONF_FILTER_NAME = f"{STACK_NAME}-VocabFilterName"
+CONF_KENDRA_INDEX_ID = f"{STACK_NAME}-KendraIndexId"
+CONF_WEB_URI = f"{STACK_NAME}-WebUiUri"
+CONF_TRANSCRIBE_API = f"{STACK_NAME}-TranscribeApiMode"
+CONF_REDACTION_TRANSCRIPT = f"{STACK_NAME}-CallRedactionTranscript"
+CONF_REDACTION_AUDIO = f"{STACK_NAME}-CallRedactionAudio"
+CONF_CALL_SUMMARIZATION = f"{STACK_NAME}-CallSummarization"
 
 # Parameter store fieldnames used by bulk import
-BULK_S3_BUCKET = "BulkUploadBucket"
-BULK_JOB_LIMIT = "BulkUploadMaxTranscribeJobs"
-BULK_MAX_DRIP_RATE = "BulkUploadMaxDripRate"
+BULK_S3_BUCKET = f"{STACK_NAME}-BulkUploadBucket"
+BULK_JOB_LIMIT = f"{STACK_NAME}-BulkUploadMaxTranscribeJobs"
+BULK_MAX_DRIP_RATE = f"{STACK_NAME}-BulkUploadMaxDripRate"
 
 # Transcribe API Modes
 API_STANDARD = "standard"
diff --git a/pca-ui/cfn/lib/api.template b/pca-ui/cfn/lib/api.template
index d30f42a1..2e357068 100644
--- a/pca-ui/cfn/lib/api.template
+++ b/pca-ui/cfn/lib/api.template
@@ -33,14 +33,17 @@ Parameters:
   
   GenAIQueryBedrockModelId:
     Type: String
-    Default: anthropic.claude-3-haiku-20240307-v1:0
+    Default: us.amazon.nova-lite-v1:0
     AllowedValues:
       - anthropic.claude-3-haiku-20240307-v1:0
       - anthropic.claude-3-sonnet-20240229-v1:0
-      - amazon.titan-text-express-v1
-      - anthropic.claude-v1
-      - anthropic.claude-instant-v1
-      - anthropic.claude-v2
+      - us.amazon.nova-micro-v1:0
+      - us.amazon.nova-lite-v1:0
+      - us.amazon.nova-pro-v1:0
+      - us.anthropic.claude-3-5-haiku-20241022-v1:0
+      - us.anthropic.claude-3-5-sonnet-20241022-v2:0
+      - eu.anthropic.claude-3-5-sonnet-20240620-v1:0
+      - apac.anthropic.claude-3-5-sonnet-20240620-v1:0
     Description: (Optional) If 'GenAIQuery' is BEDROCK, which Bedrock model to use. (Bedrock preview access only)
 
   FetchTranscriptArn:
@@ -301,11 +304,18 @@ Resources:
               - 'dynamodb:GetItem'
           - Sid: InvokeBedrock
             Effect: Allow
-            Action: 
+            Action:
               - bedrock:InvokeModel
             Resource:
-              - !Sub "arn:${AWS::Partition}:bedrock:*::foundation-model/*"
-              - !Sub "arn:${AWS::Partition}:bedrock:*:${AWS::AccountId}:custom-model/*"
+              - !Sub arn:${AWS::Partition}:bedrock:*::foundation-model/*
+              - !Sub arn:${AWS::Partition}:bedrock:*:${AWS::AccountId}:custom-model/*
+              - !Sub arn:aws:bedrock:${AWS::Region}:${AWS::AccountId}:inference-profile/*
+          - Sid: BedrockGetInferenceProfile
+            Effect: Allow
+            Action:
+              - bedrock:GetInferenceProfile
+            Resource:
+              - !Sub arn:aws:bedrock:${AWS::Region}:${AWS::AccountId}:inference-profile/*
           - !If 
               - HasAnthropicSummary
               - Sid: SecretsManagerPolicy
diff --git a/pca-ui/cfn/pca-ui.template b/pca-ui/cfn/pca-ui.template
index 094bb9cb..cca29860 100644
--- a/pca-ui/cfn/pca-ui.template
+++ b/pca-ui/cfn/pca-ui.template
@@ -3,18 +3,22 @@ AWSTemplateFormatVersion: "2010-09-09"
 Description: Amazon Transcribe Post Call Analytics - PCA UI
 
 Parameters:
+  ParentStackName:
+    Type: String
+    Description: Name of the parent stack
+
   AdminUsername:
     Type: String
     Default: "admin"
     Description: (Required) Username for admin user
-    
+
   AdminEmail:
-      Type: String
-      Description: >-
-        (Required) Email address for the admin user. Will be used for logging in and for setting the admin password. 
-        This email will receive the temporary password for the admin user.
-      AllowedPattern: ".+\\@.+\\..+"
-      ConstraintDescription: Must be valid email address eg. johndoe@example.com
+    Type: String
+    Description: >-
+      (Required) Email address for the admin user. Will be used for logging in and for setting the admin password. 
+      This email will receive the temporary password for the admin user.
+    AllowedPattern: ".+\\@.+\\..+"
+    ConstraintDescription: Must be valid email address eg. johndoe@example.com
 
   AllowedSignUpEmailDomain:
     Type: String
@@ -26,7 +30,7 @@ Parameters:
       If left empty, signup via the web UI is disabled and users will have to be created
       using
       Cognito.
-    AllowedPattern: '^(\*||([\w-]+\.)+[\w-]{2,6}(, *([\w-]+\.)+[\w-]{2,6})*)$' 
+    AllowedPattern: '^(\*||([\w-]+\.)+[\w-]{2,6}(, *([\w-]+\.)+[\w-]{2,6})*)$'
 
   AudioBucket:
     Type: String
@@ -64,17 +68,20 @@ Parameters:
       - 'LAMBDA'
       - 'ANTHROPIC'
     Description: This is what model to use for GenAIQuery.
-  
+
   GenAIQueryBedrockModelId:
     Type: String
-    Default: anthropic.claude-3-haiku-20240307-v1:0
+    Default: us.amazon.nova-lite-v1:0
     AllowedValues:
       - anthropic.claude-3-haiku-20240307-v1:0
       - anthropic.claude-3-sonnet-20240229-v1:0
-      - amazon.titan-text-express-v1
-      - anthropic.claude-v1
-      - anthropic.claude-instant-v1
-      - anthropic.claude-v2
+      - us.amazon.nova-micro-v1:0
+      - us.amazon.nova-lite-v1:0
+      - us.amazon.nova-pro-v1:0
+      - us.anthropic.claude-3-5-haiku-20241022-v1:0
+      - us.anthropic.claude-3-5-sonnet-20241022-v2:0
+      - eu.anthropic.claude-3-5-sonnet-20240620-v1:0
+      - apac.anthropic.claude-3-5-sonnet-20240620-v1:0
     Description: (Optional) If 'GenAIQuery' is BEDROCK, which Bedrock model to use.
 
   LLMThirdPartyApiKey:
@@ -97,7 +104,7 @@ Parameters:
     Default: ''
     Type: String
     Description: External Boto3 Layer Arn to use. If none is provided, one will be created automatically via boto3.template
-    
+
   PyUtilsLayerArn:
     Default: ''
     Type: String
@@ -143,7 +150,7 @@ Resources:
         AllowedSignUpEmailDomain: !Ref AllowedSignUpEmailDomain
         WebUri: !GetAtt Web.Outputs.Uri
         Environment: !Ref Environment
-        Name: 
+        Name:
           !If
           - isMainStackNameEmpty
           - !Ref AWS::StackName
@@ -193,7 +200,7 @@ Resources:
         DeployCountName: !Ref DeployCount
         DeployCountValue: !Ref DeployCount
         # DistributionId: !GetAtt Web.Outputs.DistributionId
-        EnableGenAIQuery: !If 
+        EnableGenAIQuery: !If
           - ShouldEnableGenAIQuery
           - 'true'
           - 'false'
@@ -201,7 +208,7 @@ Resources:
   WebUriParameter:
     Type: "AWS::SSM::Parameter"
     Properties:
-      Name: WebUiUri
+      Name: !Sub ${ParentStackName}-WebUiUri
       Type: String
       Value: !GetAtt Web.Outputs.Uri
       Description: PCA Web Application URI
diff --git a/pca-ui/src/genai/index.py b/pca-ui/src/genai/index.py
index a04893ba..35e9a063 100644
--- a/pca-ui/src/genai/index.py
+++ b/pca-ui/src/genai/index.py
@@ -12,6 +12,7 @@
 import requests
 import urllib.parse
 from botocore.exceptions import ClientError
+from botocore.config import Config
 
 AWS_REGION = os.environ["AWS_REGION_OVERRIDE"] if "AWS_REGION_OVERRIDE" in os.environ else os.environ["AWS_REGION"]
 QUERY_TYPE = os.getenv('QUERY_TYPE', 'DISABLED')
@@ -44,77 +45,43 @@ def get_third_party_llm_secret():
 
 def get_bedrock_client():
     print("Connecting to Bedrock Service: ", BEDROCK_ENDPOINT_URL)
-    client = boto3.client(service_name='bedrock-runtime', region_name=AWS_REGION, endpoint_url=BEDROCK_ENDPOINT_URL)
+    client = boto3.client(
+        service_name='bedrock-runtime', 
+        region_name=AWS_REGION, 
+        endpoint_url=BEDROCK_ENDPOINT_URL,
+        config=Config(retries={'max_attempts': 50, 'mode': 'adaptive'})
+    )
     return client
-    
-def get_bedrock_request_body(modelId, parameters, prompt):
-    provider = modelId.split(".")[0]
-    request_body = None
-    if provider == "anthropic":
-        print(modelId)
-        if 'claude-3' in modelId:
-            request_body = {
-                "max_tokens": MAX_TOKENS,
-                "messages": [{"role": "user", "content": prompt}],
-                "anthropic_version": "bedrock-2023-05-31"
-            }
-        else:    
-            request_body = {
-                "prompt": prompt,
-                "max_tokens_to_sample": MAX_TOKENS
-            } 
-        request_body.update(parameters)
-    elif provider == "ai21":
-        request_body = {
-            "prompt": prompt,
-            "maxTokens": MAX_TOKENS
-        }
-        request_body.update(parameters)
-    elif provider == "amazon":
-        textGenerationConfig = {
-            "maxTokenCount": MAX_TOKENS
-        }
-        textGenerationConfig.update(parameters)
-        request_body = {
-            "inputText": prompt,
-            "textGenerationConfig": textGenerationConfig
-        }
-    else:
-        raise Exception("Unsupported provider: ", provider)
-    return request_body
-
-def get_bedrock_generate_text(modelId, response):
-    print("generating response with ", modelId)
-    provider = modelId.split(".")[0]
-    generated_text = None
-    if provider == "anthropic":
-        if 'claude-3' in modelId:
-            response_raw = json.loads(response.get("body").read().decode())
-            generated_text = response_raw.get('content')[0].get('text')
 
-        else:
-            response_body = json.loads(response.get("body").read().decode())
-            generated_text = response_body.get("completion")
-    elif provider == "ai21":
-        response_body = json.loads(response.get("body").read())
-        generated_text = response_body.get("completions")[0].get("data").get("text")
-    elif provider == "amazon":
-        response_body = json.loads(response.get("body").read())
-        generated_text = response_body.get("results")[0].get("outputText")
-    else:
-        raise Exception("Unsupported provider: ", provider)
+def get_bedrock_generate_text(response):
+    generated_text = response["output"]["message"]["content"][0]["text"]
     generated_text = generated_text.replace('```','')
     return generated_text
 
-def call_bedrock(parameters, prompt):
+def call_bedrock(prompt, temperature, max_tokens):
     global bedrock_client
     modelId = BEDROCK_MODEL_ID
-    body = get_bedrock_request_body(modelId, parameters, prompt)
-    print("ModelId", modelId, "-  Body: ", body)
+
+    print(f"Bedrock request - ModelId: {modelId} Temperature: {temperature} Max Tokens: {max_tokens}")
+    
     if (bedrock_client is None):
         bedrock_client = get_bedrock_client()
-    response = bedrock_client.invoke_model(body=json.dumps(body), modelId=modelId, accept='application/json', contentType='application/json')
-    generated_text = get_bedrock_generate_text(modelId, response)
+
+    message = {
+        "role": "user",
+        "content": [{"text": prompt}]
+    }
+
+    response = bedrock_client.converse(
+        modelId=modelId,
+        messages=[message],
+        inferenceConfig={
+            "maxTokens": max_tokens,
+            "temperature": temperature
+        }
+    )
+    
+    generated_text = get_bedrock_generate_text(response)
     return generated_text
 
 def get_template_from_dynamodb():
@@ -164,10 +131,8 @@ def generate_bedrock_query(transcript, question):
 
     prompt = prompt.replace("{transcript}", transcript)
     prompt = prompt.replace("{question}", question)
-    parameters = {
-        "temperature": 0
-    }
-    generated_text = call_bedrock(parameters, prompt)
+
+    generated_text = call_bedrock(prompt, 0, MAX_TOKENS)
 
     return generated_text