You’ve developed your ML model and now are ready to take it into production. POWERON Production Machine Learning builds and deploys a robust ML stack ready for automated application integration to efficiently solve your business problems.
POWERON Production Machine Learning achieves full implementation across four milestones:
- Milestone 1: Requirements review
Identify functional requirements with data sources and infrastructure needs and review customer business workflows. - Milestone 2: Design and implement
Designing the production scale pipeline with training schedule and infrastructure deployment. - Milestone 3: Operationalize pipeline
Add CI/CD, monitoring and alerting; align with SLAs. - Milestone 4: UAT and documentation
Perform user testing with typical end users and full documentation handoff.
Deliverables for Production ML
- ML pipeline and infrastructure deployment
Your ML solution built and deployed into production in accordance with MLOps best practices. - Technical Design Document
Detailed inventory of Google Cloud configurations options, decisions, and recommendations for deployment. - Orchestration code
Code and scripts extensible for additional pipeline deployments. - Training plan
List of recommended courses for key staff.