Swiss Life is a leading European provider of life insurance and retirement solutions, employing nearly 10,000 people. As the organization increased its focus on AI-driven innovation and regulatory compliance, it recognized the need to modernize how data was documented, governed, and shared across teams.
To support enterprise-wide decision-making and scalable AI initiatives, Swiss Life launched a transformation program aimed at unifying data practices, clarifying ownership, and making trusted data accessible across the organization.
A core principle guided this initiative: AI and innovation can only scale when the underlying data is transparent, governed, and aligned with business objectives.
Challenges
Swiss Life’s growing data and AI landscape created several organizational and technical challenges:
- Fragmented documentation across multiple systems
- Limited visibility into how data was sourced, transformed, and reused
- Unclear data ownership across teams
- Difficulty industrializing and reusing AI and data science assets
- Regulatory and compliance requirements requiring stronger traceability
- Need to align technical and business stakeholders around shared definitions
The organization needed a platform capable of structuring metadata, documenting AI assets, and supporting collaboration between data, IT, and business teams.
Why DataGalaxy
Swiss Life selected DataGalaxy based on three key criteria:
- Strong alignment with business needs and governance objectives
- User-friendly interface accessible to both technical and non-technical users
- Ability to document and connect data assets, lineage, and AI use cases within a unified environment
This combination enabled Swiss Life to transform scattered knowledge into a shared and actionable data foundation.
“Thanks to DataGalaxy, we can finally track data end-to-end and identify data ownership. DataGalaxy’s Data Knowledge Catalog has provided so many benefits for our organization, including a fully documented functional and technical use case, a thorough algorithm library, and a clear identification of ownership between IT, business, data, and BI teams.”
DataGalaxy implementation
Swiss Life adopted an agile implementation approach.
The teams:
- Conducted a technical inventory across 17 systems
- Documented and structured 30 key data assets
- Built a roadmap for documenting and reusing data science and AI assets
- Mapped data sourcing, transformation, and sharing processes
- Clarified data ownership and governance responsibilities
By centralizing definitions and documenting reusable AI components within an AI algorithm library, Swiss Life created transparency around the data powering its models and reports.
Outcomes
With DataGalaxy, Swiss Life is now able to:
- Accelerate the delivery of AI use cases
- Improve productivity across data and business teams
- Ensure stronger regulatory compliance and data quality confidence
- Provide complete transparency into data lineage
- Promote reuse of data science and AI assets
- Support broader data democratization across the enterprise
As a result, Swiss Life has strengthened cross-functional collaboration and established data as a strategic enabler of innovation and long-term growth.
Key takeaway
Scalable AI requires structured, transparent, and governed data.
By centralizing data knowledge, clarifying ownership, and documenting AI assets, DataGalaxy enables Swiss Life to accelerate innovation while ensuring compliance, trust, and enterprise-wide alignment.
