The AI Lab is a central hub for managing, optimizing, and monitoring AI projects. It provides a range of functionalities that facilitate building and deploying AI-driven solutions.

Templates

The Template section is where users define and map data points and properties. It serves as the registration area for digital twins, allowing multiple twins to be mapped and managed simultaneously. This setup supports various AI models and solutions.

Pipelines

Pipelines represent a sequence of steps that define the solution process. These steps can include querying data, transforming it, running machine learning models, and visualising results with plots. Each pipeline is customisable, depending on the problem being addressed.

Experiments

Experiment is used to monitor and test pipeline executions before they are scheduled with triggers. This section includes visualisations such as plots that help users understand if their pipelines are functioning as expected. It ensures that AI models and transformations are tested in a controlled environment.

Triggers

The Trigger feature allows pipelines to be executed in real time based on user-defined intervals. Users can schedule when pipelines should run automatically, ensuring that data processing and analysis happen at the right time without manual intervention.

Execution Logs

The Execution Logs section displays the status of all pipelines that have been executed. Users can access detailed information, such as which twin the pipeline ran on, start and end times, total execution time, and any waiting periods. This section provides valuable insights into the performance and progression of AI workflows.