Phase 06 of the Data Science Lifecycle
From Model to Production System
A model only creates value when it actively supports decisions in production.
From Prototype to Production
Deployment is a continuous process. We ensure reliable, maintainable operations.
Infrastructure
Production deployment – scalable and highly available.
Monitoring
Continuous monitoring with automated alerts.
Continuous Improvement
Processes for model updates as requirements change.
Our Approach
Productionisation
Preparing for production use with interfaces and quality checks.
Automated Release
Traceable deployment process with tests and rollback options.
Monitoring & Alerting
Early detection of changes in model performance and data quality.
Operations Handover
Knowledge transfer, documentation, and process establishment for your team.
Typical Deliverables
Production-ready ML system
Automated deployment process
Monitoring and observability concept
Operations documentation and knowledge transfer
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