A centralized ML operations and governance tool empowering organizations in the deployment, operationalization and maintenance of their ML models.

Whom is ML Manager™ for?


For organizations who:

Have a ML and AI model portfolio and want to operationalize and scale it up while remaining in control of it.

Have growing ML and AI assets and want to deploy them while minimizing cost and effort.

Want to deploy, maintain, and manage their ML and AI models effortlessly, regardless of the current or future platform on which they are developed.

Have a patchwork of model scoring and validation they don’t want to manually run anymore.

Want to free up scarce data science resources to create more and better models.

For organizations who:

Have a ML and AI model portfolio and want to operationalize and scale it up while remaining in control of it.

Have growing ML and AI assets and want to deploy them while minimizing cost and effort.

Want to deploy, maintain, and manage their ML and AI models effortlessly, regardless of the current or future platform on which they are developed.

Have a patchwork of model scoring and validation they don’t want to manually run anymore.

Want to free up scarce data science resources to create more and better models.

FEATURES & ADVANTAGES


Full Control

With ML Manager™, you get the full view and control of all your ML and AI models with an integrated governance tool for your ML operations.

Easy Monitoring

Better monitor your ML production pipeline and model performance using production dashboards, reporting and model diagnostics to identify and address potential data, process and model deficiencies.

Automating

Schedule, orchestrate and automate your ML operation pipelines in order to reduce manual interventions and wasteful task coordination.

KEY BENEFITS


Minimize Time & Effort

Minimize the time and effort spent in deploying ML models, understanding their state, managing and maintaining them in production.

Leverage Disparate ML Tech

More easily leverage your disparate ML technologies as ML Manager™ is language agnostic.

Speed Up Delivery Time

Speed up your delivery time by avoiding conversion of models from one platform to another in order to deploy to production.

Free Up Data Scientists

Free your data science team so that they work on advancing your ML models instead of spending time on ML operationalization and maintenance work.

Maximize Profits

Maximize profits and minimize losses by delivering quality predictive insights on time, in a consistent and scalable fashion.

FEATURES & ADVANTAGES


Full Control

With ML Manager™, you get the full view and control of all your ML and AI models with an integrated governance tool for your ML operations.

Easy Monitoring

Better monitor your ML production pipeline and model performance using production dashboards, reporting and model diagnostics to identify and address potential data, process and model deficiencies.

Automating

Schedule, orchestrate and automate your ML operation pipelines in order to reduce manual interventions and wasteful task coordination.

KEY BENEFITS


Minimize Time & Effort

Minimize the time and effort spent in deploying ML models, understanding their state, managing and maintaining them in production.

Leverage Disparate ML Tech

More easily leverage your disparate ML technologies as ML Manager™ is language agnostic.

Speed Up Delivery Time

Speed up your delivery time by avoiding conversion of models from one platform to another in order to deploy to production.

Free Up Data Scientists

Free your data science team so that they work on advancing your ML models instead of spending time on ML operationalization and maintenance work.

Maximize Profits

Maximize profits and minimize losses by delivering quality predictive insights on time, in a consistent and scalable fashion.

Using ML Manager™

5 steps to ML Operationalization and Governance at scale.


Connect your existing database and ML servers :

  • Centralized management and governance of your ML operations.
  • Support of your entire data science technology stack.
  • Inventory of the database and ML engine servers involved in your ML operations.

Register your data, ETL processes and ML models for building your ML pipelines :

  • Inventory of your machine learning models.
  • Inventory of the model associated data ETL processes.
  • Inventory of the data tables involved in your ML pipelines.

Deploy and serve models as batch processes or APIs :

  • Standardized deployment steps for all batch processes and web APIs.
  • Centralized scheduling and orchestration for all your ML models and ETL processes running across your entire data science technology stack.

Manage and Govern your ML Operations :

  • Production dashboards that inform you of the state of your machine learning models, their execution, and the execution of their associated data ETL processes.
  • Production reports that help you understand your machine learning production process from start to end.
  • Alerting system that informs you of model operationalization issues.

Scale your ML portfolio :

  • Automatic quality insurance check on data prior to the execution of the model.
  • Monitoring of the state and readiness of the data needed to execute models.
  • Monitoring of the state and readiness of ML models.


Want to know more about what ML Manager™ can actually do for your business?

REQUEST YOUR DEMO WITH DAESYS