The AI/ML journey from plan, design & development to deployment & operations
Develop AI/ML Solutions
Plan
- Identify use case and the outcome, Define scope and success criteria
- Identify the target area, either from pre-defined industry use cases or from a company specific pain point
- Identify data sources, Review data dictionaries, making sure the data aligns with use case requirements
- Confirm understanding of current data pipeline, tools & architecture
- Deliver a project plan
Build
- Execute the Data & AI process and develop the solution
- Data engineering to assemble, clean, normalize, cleanse and consolidate
- Iterate over augmented intelligence to ensure data quality SLAs are met
- Build the use case using EazyML UI and/or API or the Analytics toolset. Ensure that the SLAs for insights confidence score and/or model performance are met
- Weekly cadence and Readouts
Operate
- Review KPIs, Identify success/risk factors for rollout
- Deliver and review operation plan with Customer IT (op-prem, cloud)
- Assist Customer IT w/implementing the operation plan
- Provide user training, assist w/UAT
- Actively manage & run the programs
- Continuous monitoring and support