AI model management and governance just got easier.
Having a handle on how AI is being used within your organization is no longer a dream – the Modzy platform allows you real-time insight into and management of all of your AI models at scale. Eliminate risks from ‘Shadow AI’ with a comprehensive AI model management system, recognized by industry analysts such as Gartner and Cognilytica for its capabilities in MLOps, ModelOps and model management.
Modzy provides a mechanism for managing the lifecycle of model creation and operationalization (MLOps), as well as ModelOps, which focuses on the governance and lifecycle management of models. We monitor performance in real-time, as well as managing ongoing governance and security, with audit functionality to meet any compliance needs for your industry.
In line with industry best practices, Modzy offers the following key AI model management features:
Manifests include the model, dependencies, inference scripts, sample data
Tracking models in production, such as model performance metrics, model runtimes, and success rates to identify when retraining is necessary
Modzy’s approach to AI model management enables embedded governance, which allows you to maintain a centralized view of how AI is being used across your enterprise in real-time.
- Track AI usage 24/7 through our Model Operations Dashboard and detailed audit logs
- Keep your AI on lock with roll-based access controls (RBACs), API key management tools, and custom authentication options
- Avoid the pitfalls of consumption-based pricing with real-time insight into model operations, performance, infrastructure usage, and costs
- Ensure only the best AI models are approved for enterprise use with custom approval workflows
- Accessibility is must for today’s diverse workforce, and Modzy is compliant with WCAG 2.0 Level AA Success Criteria
Key AI stakeholders love Modzy’s approach to AI model management.
- Quick process to package and deploy models, with automatic versioning
- Model monitoring helps to identify when a model drifts significantly and it’s time for retraining
- Infrastructure control to easily specify required resources for deployment
- Easily integrate AI models into existing applications with a few lines of code via our APIs and SDKs
- Customizable model auto-scaling to allow you to control how your infrastructure is used and reduce latency for high-frequency jobs
- Centralized location for AI management across the enterprise, as well as a way to identify any duplication of efforts and opportunities for cost savings
- Easy way to access performance and audit logs for compliance purposes
- Role-based access controls and better approach for managing AI security