Studio for Model Libraries Creation
Cosmo Tech’s Studio is a graphical, low-code tool designed for developers and modelers who are experts in systems modeling using CosML. The Studio comes with domain libraries pre-installed to speed up the development and deployment of the Enterprise Digital Twin. The graphical user interface allows users to create the system, its subsystems, their entities, their rules and behaviors, and the interconnections between the sub-models quickly and easily.
Studio for Simulation Engine Configuration
Once a conceptual model has been defined, the Studio automatically generates and builds the simulation engine that includes the code and rules of the conceptual model. Our model-driven software platform will then automatically generate data structures and APIs to connect web and third-party applications. The simulation engine can be configured and made available to data integrators.
The highly-configurable simulation engine ensures easy replication and operationalization of a solution for a given use case from one customer to another. The process only requires the representation of the existing one to a new data set describing the specificities of the new customer situation.
Datalab for Pre-Processing Extensions
Cosmo Tech’s Datalab tool, based on the Jupyter Notebook and comprehensive Python APIs, allows for advanced data preparation by:
- building pipelines of data transformation and combining various sources of data including time series data, enterprise system data, IoT and data analytics platforms, etc.
- gaining visibility on prepared data at any stage of the user’s transformation
- feeding data for Enterprise Digital Twin instantiation calibrating Enterprise Digital Twin parameters
- using built-in or third party data science libraries
Datalab for Post-Processing Extensions
The Cosmo Tech Datalab tool offers access to Enterprise Digital Twin insights with advanced data exploration capabilities, including:
- building custom KPIs to extract new actionable insights
- relying on built-in or third party data science libraries to identify correlations
- benefiting from full visibility of cascading effects and their explainability
- visualizing simulation outputs with custom reporting views
- exporting data to third party systems
Datalab for Simulation-based Analytics
- Use Datalab’s protocol extension for real-time combinations of simulation and data science libraries
- Create algorithms such as robustness testing, sensitivity analysis, or parameter optimization under constraints
- Support state of the art data science libraries such as machine learning, scientific computing, optimization, and experimental design
APIs for custom applications
REST APIs are available at runtime to access any model data from any authorized host, as well as control the execution of the simulation and experiments.
Python APIs are also available to access and develop interactive or graphical extensions such as pre-processing or post-processing dashboards.