MLOps Launchpad - 2 Weeks Assessment

About SoftServe

SoftServe is a digital authority operating at the cutting edge of technology. With expertise across healthcare, retail, media, financial services, manufacturing, and software, we implement end-to-end solutions, delivering the innovation, quality, and speed that our clients' users expect.

About MLOps Launchpad

MLOps Launchpad operationalizes and scales machine learning workloads through modern MLOps practices, governance, and automation. It assesses ML maturity, establishes Azure ML deployment patterns, operationalizes selected workloads, and defines the governance and lifecycle practices needed to scale ML across teams.

What Makes a Difference

• Operationalization First - moves models from notebooks to production with repeatable train/deploy/monitor patterns
• Governance Built-In - ownership, approval gates, and auditability across training, deployment, and monitoring
• Azure-Native - built around Azure Machine Learning, aligned to Microsoft reference architecture and security standards
• Modular - start with assessment, foundation, or one workload, then expand to reusable MLOps capabilities

Engagement Path

• ML Readiness Assessment - 2 weeks maturity assessment, prioritized workload backlog, target-state architecture, roadmap
• Pilot Workload Operationalization - 5 weeks one workload packaged, trained, and deployed with CI/CD, model registry, monitoring
• MLOps Foundation - 7 weeks reusable Azure ML platform for experiment tracking, pipelines, deployment automation, access control
• Scale, Governance & Lifecycle - 12+ weeks operating model for scaling ML: governance, lifecycle policies, production support handover

Important Notes

Cost and timeline can fluctuate depending on the project's scope and complexity in alignment with the customer's needs.