Story
AWS
Edwards LifesciencesEdwards Lifesciences Standardizes Model Serving on AWS
Edwards Lifesciences, a health care organization in the United States, uses Amazon S3 from AWS to support applied AI delivery for ML and product teams.
Value results
| Category | Value result |
|---|---|
| Capability | Applied AI delivery stays visible to adjacent teams through Amazon S3 |
| Capability | ML and product teams work from the same Amazon S3 record for model serving |
| Capability | Model serving can be reviewed without waiting on a personal export |
Story
Edwards Lifesciences is based in the United States and runs health care operations at a scale where model serving cannot live in side channels. ML and product teams were reconciling competing copies of the same work, which slowed applied AI delivery and hid who owned the next step.
The company runs applied AI delivery on AWS, with Amazon S3 as the product ML and product teams actually open. Amazon Web Services is the leading public cloud for compute, storage, data, and AI services, used to run production systems at global scale. For Edwards Lifesciences, that means ML and product teams can open one workflow, see model serving, and let neighboring teams join without inventing a parallel stack.
Public materials confirm the companies and products. They do not always publish a single verified KPI for this pairing, so the outcome here is operational: clearer ownership, fewer stalled handoffs, and a shared record for model serving.
