Amazon SageMaker advances governance as Swiss Life scales AI

How Swiss Life Germany automated governance and collaboration with SageMaker

Swiss Life Germany is automating data governance and collaboration with Amazon SageMaker Unified Studio. The approach centralizes data discovery, cataloging, and access control so teams can find, request, and use the right data with consistent guardrails.

In practice, the program focuses on governed discovery through the SageMaker Catalog, standardized metadata and lineage to preserve provenance, and role-based permissions that extend across general-purpose Amazon S3 storage and cataloged datasets. The intent is to enable cross-team reuse while maintaining traceability and minimizing manual policy work.

Why SageMaker Catalog and lineage matter for compliance

According to AWS, SageMaker Catalog now supports read/write access to general-purpose Amazon S3 buckets and can ingest metadata from AWS Glue Data Catalog in real time. Taken together, these capabilities align permissions with storage locations, keep schema and business context synchronized, and record how assets move between teams.

For a regulated insurer, that combination matters because compliance relies on clear ownership, auditable lineage, and least-privilege access. When metadata, lineage, and access decisions sit in one governed catalog, it becomes easier to demonstrate control design to auditors, reproduce model inputs, and enforce separation of duties across analytics and ML workflows.

Immediate outcomes at Swiss Life Germany after AWS modernization

According to Deloitte, Swiss Life Deutschland migrated more than 1 PB of data, 324 workloads, and legacy applications to AWS, establishing a cloud foundation for its data and AI strategy. That modernization reduces undifferentiated operations and provides standardized security guardrails that SageMaker can inherit.

The business objective behind the move was agility and customer impact, as the company’s technology leadership emphasized in the same case study. “By using cloud technology, we can also be agile to market changes, offer new technologies to sales, and maximize the benefits for our customers,” said Dr. Tobias Herwig, CTO, Swiss Life Deutschland.

Early outcomes at Swiss Life Germany include faster data access for practitioners, clearer discoverability of approved datasets, and controlled sharing across product teams, consistent with the Unified Studio model. Public materials reviewed to date do not detail bias and explainability tooling or drift monitoring inside Swiss Life’s workflows, so the precise model-governance setup remains undisclosed.

At the time of this writing, Amazon.com, Inc. (AMZN) traded at 208.78, up 1.71%, as of 3:21:27 PM EST, based on data from Yahoo Scout. This neutral backdrop situates the vendor context for the AWS services underpinning Swiss Life’s platform.

Unified Studio features enabling governed data sharing

As reported by TechTarget, SageMaker’s Unified Studio brings analytics, machine learning, data management, and AI development into one environment with built-in governance controls such as the SageMaker Catalog, lineage tracking, and role-based access. This consolidates the tasks of finding, evaluating, and sharing data so both technical and business teams can collaborate without abandoning compliance.

Swiss Life Germany’s internal framing underscores that goal of democratized, governed access. “The launch of SageMaker Unified Studio comes at the perfect time for Swiss Life. It is a great product that will simplify the main goal: Bring data to the people that really need it. The ability to connect various data sources, easily share them with another team or product and use the full power of the underlying AWS infrastructure will take data science at Swiss Life to the next level,” said Simon Mannstein, Team Lead Cloud Platform & Adoption, Swiss Life Deutschland.