Deploy GenAI models with repeatable pipelines and clear governance
Model performance only matters if teams can deploy, monitor, and maintain models reliably in production. This workshop helps leaders establish core MLOps practices, apply.
Leave with an MLOps blueprint—pipeline approach, release process, monitoring plan, and governance model.
The Challenge
Many organizations can train models, but struggle to operationalize them with production discipline.
- Pipelines are inconsistent: Model delivery depends on manual steps and team-specific workflows that are hard.
- Releases are risky: Without clear gates and rollback readiness, deploying new models can disrupt users.
- Monitoring and ownership are unclear: Teams lack agreed signals, response playbooks, and governance to keep models reliable.
Without MLOps, models become fragile in production—slowing iteration and increasing operational risk.
Our Solution
We guide your team through a practical approach to operationalize GenAI models with repeatable pipelines, safe deployment practices.
- Core MLOps Principles and Operating Approach: Align on how MLOps should work across teams, including roles, standards.
- ML Pipelines and CI/CD Integration: Define how models move from development to production through repeatable build, test.
- Production Deployment for Fine-Tuned Models: Establish deployment patterns, quality gates, and rollout methods appropriate for enterprise environments.
- Monitoring and Maintenance Protocols: Define what to monitor, how to detect issues early, and how.
- Governance for Deployed Models: Establish governance expectations for approvals, documentation, auditability, and ongoing model assurance.
Area of Focus
- Core MLOps Principles and Best Practices for ML Pipelines
- Applying CI/CD Techniques to Model Integration and Deployment
- Deploying Fine-Tuned Models into Production Environments
- Implementing Monitoring and Maintenance Protocols
- Establishing Governance for Deployed Models
Participants Will
- Define an MLOps approach that standardizes model delivery across teams and use.
- Establish CI/CD-aligned workflows to reduce manual effort and improve release reliability.
- Identify deployment patterns and quality gates to ship fine-tuned models safely.
- Define monitoring and maintenance protocols that sustain performance in production.
- Leave with a governance model that clarifies ownership, approvals, and ongoing assurance.
Who Should Attend:
Solution Essentials
Format
Facilitated workshop (in-person or virtual)
Duration
4 hours
Skill Level
Intermediate to Advanced
Tools
Slides, workshop templates, key worksheets, checklists, and collaboration tools.