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Extensibility with Wize Analytics
Expand Wize Analytics’ native capabilities with custom components and amplify your impact on business outcomes.
Public and Proprietary Plugins
Wize Analytics provides the flexibility to package custom code components in a GUI and share them with others as plugins. These specialized components extend Wize Analytics’ native functionality in a seamless way for end-users, with custom visual recipes, datasets and connectors, webapps, processors, and more.
Custom ML
Advanced data scientists can extend the visual ML interface by adding a custom Python algorithm, or programmatically develop models using Python, R, Julia and other languages. To ensure external efforts are captured and interpretable to the rest of the team, Wize Analytics captures the details of these experiments and automatically provides model comparisons and explainability reports.
Regardless of where a model is developed, Wize Analytics remains the central platform for deployment, monitoring, and governance.
CI/CD with APIs for DevOps
Robust APIs enable IT and ML operators to programmatically perform Wize Analytics operations from external orchestration systems and incorporate these tasks into existing data workflows. Wize Analytics integrates with the tools that DevOps teams already use, like Jenkins, GitLabCI, Travis CI, or Azure Pipelines.
Custom Web Apps
Wize Analytics supports interactive web app development from design to delivery, so business audiences can interactively use data and predictive insights to drive better customer experiences and outcomes.
Configure pre-built visual templates or code a fully custom web app using leading data science visualization frameworks such as Dash, Bokeh, R Shiny, JavaScript, and Streamlit.
Regardless of where a model is developed, Wize Analytics remains the central platform for deployment, monitoring, and governance.