Tardigrade AI enables organizations to anticipate their exposure to climate hazards by transforming complex scientific data into precise financial risk indicators.The company migrated from university supercomputer hosting to Google Cloud for a scalable, flexible platform using BigQuery, Cloud Run, Cloud SQL, Cloud Storage, Cloud Workflows, and Pub/Sub.Gemini AI models interpret complex climate and econometric data into accessible language, generating automated client reports with actionable insights and recommendations.The platform scales dynamically with Cloud Run to control costs and handle varying workloads, while ensuring GDPR compliance.Future developments include natural language querying of BigQuery with Gemini and integration with tools like Looker and Google Earth for dynamic visualization.
Sanitas, one of Switzerland's largest health insurers, modernized its 19-year-old legacy Oracle data warehouse, which was causing critical delays for healthcare analytics with 24-hour batch processing cycles.They collaborated with Google Cloud and partner ipt to migrate to a modern lakehouse architecture based on BigQuery with real-time ingestion, automated data pipelines, CI/CD integration, and layered data governance compliant with healthcare regulations.The new architecture leveraged Cloud Datastream, Dataplex, Cloud Composer, and innovative BigQuery features like table cloning for parallel development.Sanitas deployed eight production AI services, including a Sales Assistant built with Vertex AI providing real-time personalized product recommendations integrated within CRM workflows.The solution reduced data warehouse costs by 25%, eliminated downtime during migration, enabled real-time analytics (previously daily batch), and improved agility and decision-making across multiple business domains.
A global automotive manufacturer modernized its data and analytics capabilities by migrating to Azure. Facing organizational and technical barriers that slowed cloud migration and the adoption of AI-driven analytics, the company collaborated on a comprehensive blueprint. Key components included centralizing data in Azure Data Lake, leveraging Azure Databricks, Unity Catalog, and MLflow for improved data orchestration, and onboarding hundreds of data practitioners. The initiative enabled scalable, real-time analytics, automated KPIs, and rapid experimentation. Digital transformation now spans multiple operational areas, including marketing analytics, media investments, and IoT-based telemetry. Enhanced data security, automation, and centralized infrastructure have provided a robust platform for ongoing AI innovation and business optimization across the enterprise.