MLOps for Risk and Compliance Professionals
Gain confidence in your organization’s ability to mitigate risk and ensure compliance with model validation and governance.
The Advantage of MLOps for Risk and Compliance Departments
MLOps is a solution that allows teams to control their models automatically with a single, centralized hub to deploy, monitor, and update models in a consistent way.
MLOps can help risk and compliance professionals in these four areas:
Deployment
MLOps makes model deployment easy. Operations teams, not data scientists, can deploy models written in a variety of modern programming languages like Python and R onto modern runtime environments in the cloud or on-premise. Users of the MLOps system don’t have to know any of these technologies to drag and drop a model into the system, create a container, and deploy the model to a production environment.
Monitoring
MLOps gives you monitoring that is designed for machine learning. Monitoring includes service health, data drift, model accuracy, and proactive alerts that are sent to stakeholders using a variety of channels like email, Slack, and Pagerduty. With MLOps monitoring in place, your teams can deploy and manage thousands of models, and your business will be ready to scale production AI.
Production Lifecycle Management
Models need to be updated frequently and seamlessly. MLOps model lifecycle management supports the testing and warm-up of replacement models, A/B testing of new models against older versions, seamless rollout of updates, failover procedures, and full version control for simple rollback to prior model versions.
Production Model Governance
MLOps governance provides the integrations and capabilities you need to ensure consistent, repeatable, and reportable processes for your models in production. Key capabilities include access control for production models and systems, including integration to LDAP and role-based access control systems (RBAC), as well as approval flows, logging, version storage, and traceability of results for legal and regulatory compliance.
The Need for an Enterprise-Level MLOps Strategy
Strategy is important, especially when it comes to monitoring models in production and scaling and generating value from AI. In a recent conversation with Forrester, we discussed the strategic components required for buy-in across all functions in the company and how to support business applications.
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MLOps Customers
Companies across every industry leverage DataRobot’s MLOps solution, such as:
