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-# Integrations
-
-This collection of guides outlines various integrations between Arthur and 3rd party services, frameworks, and platforms. Ranging from model onboarding examples to pipeline setups for automatically ingesting new inferences, these tutorials will help you quickly bring Arthur into your team's ML development lifecycle.
-
-## {doc}`SparkML Integration <sparkML>`
-This guide provides an example of integrating with the ArthurAI platform to monitor a SparkML model. 
-
-## {doc}`AWS SageMaker Data Capture Integration <sagemaker>`
-This guide walks through setting up a Sagemaker integration to send Data Capture log files to Arthur.
-
-## {doc}`PagerDuty & ServiceNow <alert>`
-This guide walks through integrating Arthur alerting with your incident response tools to streamline your model monitoring operations.
-
-```{toctree}
-:maxdepth: 2
-:hidden:
-SparkML Integration <sparkML>
-AWS SageMaker Data Capture Integration <sagemaker>
-PagerDuty & ServiceNow <alert>
-```