ModelOp Center
ModelOp Center is the industry’s only agnostic enterprise ModelOps software with a unified approach across the modern heterogenous IT ecosystem to consistently deploy, monitor, and govern enterprise models.
ModelOp Center – Microservices Architecture
Abstracting the Complexity of a Modern AI Architecture
An End-to-End Solution with Key Capabilities That Put Models in Business
Deployment:
Create a consistent and automated path to put all of your models in business, regardless of their languages, frameworks, data science workbenches, or environments.
Simply register your models into ModelOp Center via our model factory plugins, CLI, or API, and our services automate the productionization process, including packaging, running reproducible tests in approved environments, and ultimately deploying the model. No model code changes necessary!
Monitoring:
Continuously monitor and improve your models’ performance, regardless of model language, platform, or execution type. Employ statistical, technical, and business monitoring against customizable, business-specific SLAs to maximize the value to the business.
Governance:
Maintain a comprehensive model catalog that contains all of the metadata, lineage, and assets that compose each and every model for full visibility, explainability, and auditability across the enterprise.
Command Center:
Gain real-time visibility into and 24×7 control over all models. ModelOp Center’s Command Center provides a single pane of glass into the health and effectiveness of all models across the enterprise.
Operations-Focused
Technology-Agnostic
ModelOp Center operationalizes the life cycle of all types of models (AI/ML, Rule-based, Statistical, Mathematical optimization) developed in any model factory, and executed on any platform in any heterogenous technical environment.
Automated
A Model-Centric approach is the key to overcome the challenge to Scale AI
Ten years ago, most enterprises used one end-to-end platform for data, modeling, and production operations. Today, with the rapid pace of innovation of data science tools, combined with the explosion of new analytical use cases, enterprises face an exponential growth in the choice of technologies. Dozens of modeling workbenches. 100’s of combinations of data platforms, types, and structures. 100’s of new data science frameworks. Dozens of new business applications to consume models. Hybrid use of on-prem, cloud, and partner environments. Even the most advanced enterprises struggle.
