Comet, a leader in AI development tools, has partnered with Amazon Web Services (AWS) to integrate its platform into Amazon SageMaker’s newly launched partner AI apps capability. This collaboration brings Comet’s comprehensive tools for experiment tracking, large language model (LLM) evaluation, and production monitoring directly into Amazon SageMaker AI, providing developers with an all-in-one solution for managing the entire AI and ML lifecycle.
Amazon SageMaker Partner AI Apps
Amazon SageMaker AI is a fully managed service designed to simplify and scale machine learning (ML) and generative AI development. It provides developers with tools for building, training, and deploying models, including notebooks, pipelines, debuggers, and MLOps capabilities, all within a unified environment.
With the introduction of SageMaker partner AI apps, AWS enables customers to discover and use third-party applications directly integrated into the SageMaker environment. These apps run privately, meet AWS security standards, and are fully managed by AWS, removing the complexity of deployment, scaling, and upgrades so customers can focus on developing innovative AI solutions.
Comet and Amazon SageMaker AI: A Unified ML and GenAI Platform
The integration of Comet’s platform within Amazon SageMaker partner AI apps offers a seamless solution for machine learning and generative AI projects. SageMaker customers can now access Comet’s tools for experiment management, LLM evaluation, and model production monitoring directly within the SageMaker interface. Key benefits include:
- End-to-End Workflow Management: Comet integrates seamlessly into SageMaker Studio, Notebooks, and Pipelines, providing tools for tracking experiments, optimizing models, and monitoring production workflows.
- LLM-Specific Tools: Comet’s LLM evaluation platform, Opik, is included in the integration, offering automated tracking and evaluation capabilities to optimize generative AI applications.
- Holistic Deployment: Fully managed by AWS, Comet’s tools appear as part of the SageMaker Studio environment, ensuring streamlined integration without disruption to existing workflows.
- Data Privacy and Security: Deployments are securely isolated and automatically provisioned, ensuring customer data remains private while leveraging AWS’ secure infrastructure.
The partnership simplifies the ML lifecycle by combining Comet’s advanced model management capabilities with SageMaker’s robust infrastructure, enabling developers to optimize projects across experimentation, evaluation, and production phases.
“Hundreds of thousands of customers use Amazon SageMaker AI to build, train, and deploy ML and foundation models,” said Ankur Mehrotra, Director and General Manager of Amazon SageMaker AI. “We believe Comet’s capabilities for experiment tracking and model production monitoring will help accelerate our customers’ journey in building generative AI and ML models.”
“The announcement of Comet being available as a SageMaker partner AI app will simplify our technology estate and developer workflow, allowing our data scientists and ML engineers a better experience for experiment tracking, cataloging and registering models, and monitoring those models in production," commented Greig Cowan, Head of AI and Data Science Innovation at Natwest Group.
With Comet’s integration, SageMaker customers can easily manage and optimize AI models throughout their lifecycle, from initial experiments to production deployment. The collaboration between Comet and AWS ensures that ML and generative AI teams have access to best-in-class tools for improving transparency, reproducibility, and efficiency in their workflows.
