Overview
Machine Learning models impact to a business is not in doubt, but providing the the right environment to maximse the value-impact, on a ongoing, repetable and consistent manor, can be a challenge.
- Inconsistent deployment and monitoring of models across and organization.
- Slow model deployment cycle - falling behind.
- Out of date or unrefreshed models - not reliable / declining insights.
- Investment in ML & Technology is high - ROI is not matched.
- Centralized model performance management - poor or not in existance.
- Data Strategy - poor data quality, poor data pipelines, poor models, difficult workflows.
- Model performance is not always measured or is manual.
All the above can impact the execution and value of Gen AI to a business.
Where to start?
Assessing the maturity of an MLOps environment involves evaluating various aspects of the system, including: automation, scalability, reliability, and more. These are technical variables; however we also focus on processes and people to ensure a comprehensive understanding of your environment and actionable outcomes.
The following benefits can then be achieved:
- Industrialised ML accelerating speed to value
- Focus on ML innovation and not infrastructure
- Reduced infrastructure cost
- Accelerate Customer Data Integration
- Optimised Operating Model
- Customer Data Privacy
Highlights
- MLOps MATURITY LEVEL REPORT: A document which captures high level approach, governance, compliance and non-functional aspects for the initiative, as well as the high-level requirements (functional/ non-functional) of the advisory workstreams and cloud provider of preference.
- CURRENT STATE & GAPA ANALYSIS / AREAS OF IMPROVEMENT: A document which captures the current state MLOps systems/assets and identifies gaps/areas of improvement. This would focus on which components of the MLOps lifecycle can be targeted for improvement and why, and considers AWS services are used optimally for the customer’s scenario.
- SOLUTION OUTLINE & EXECUTION PLANNING: A document which captures the high-level Roadmap, Milestone, Timeline and Team Size, as well as AWS MLOps revised architecture (plus Process, Tooling, Technology & Hosting aspects), which can be used as input for planning any subsequent phases to achieve the proposed Future State solution.
Details
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Vendor support
- Standard Support: Email and chat support during business hours.
- Premium Support: 24/7 support with dedicated account management.
- Training Workshops: On-demand and live training sessions covering MLOps best practices and AWS tools usage.
Initial point of contact:
Harry Miller | Solution Director Harry.Miller@uk.globallogic.com +44 (0)7532769431 https://globallogic.com/uk