Demo: SensibleAI Forecast Express

SensibleAI Forecast Express. Let's assume I am a power user at Golfstream, a vertically integrated golf retailer. I'm preparing to kick off my revenue forecast for drivers in woods for our West Group entities.

It's January 2026, and I've just loaded my actuals for December 2025. SensibleAI Forecast allows me to source data from and write forecast results back to my cube without needing to write custom data pipelines.

Within my newly created project, I can configure my source data. Forecast Express allows me to select my cube and scenario and the time periods I want to pull my data from. Since more data generally means the better model performance, I'll pull in seven years of history.

I will select the rest of the members to pull data from, filtering results by pinning specific members, and selecting the actual line items I want to forecast for. With my dimensions selected, I can generate a preview of my data to ensure it's the data I want.

I can see the number of line items I'm forecasting for, and the amount of historical data I have for them. Once confirmed, I can submit. The new cube administration page allows me to configure the workflow responsible for loading my forecast results.

The workflow page displays the various workflows, transformation rules, and data sources in my application. Let's create some new ones for my project. I can see the existing data sources filtered by cube and scenario type.

I'll create a new one, providing a name, SensibleAI forecast, and selecting my fin detail cube and forecast scenario type. Next, I will create a new transformation rule profile. Finally, for the workflow profile, I will provide a name, select my cube root workflow profile, and submit.

Any new sources will be created automatically based on my configurations, and my workflow profile is now ready to load my forecasting results. A streamlined output configuration allows SensibleAI forecasts to write the results back to the cube as the prediction completes.

Now let's switch perspectives. As an end user, cube views are my home base, and my SensibleAI forecast results are already waiting for me. It's never been easier to access my generated forecast insights.

Looking out a few months, let's drill down into the Phoenix Mach 10 forecast for April. Drilling back, I can load the prediction summary view from SensibleAI forecast. With the full year's forecast in view, I'll hone in on April.

Below, the prediction explanation for my April forecast shows how the features impacted this result. I can view the tug of war chart to see the feature contributions across my forecast horizon, the features that increased or decreased my forecasted value.

The periodic explanations page shows an alternative view. I'll select a forecast start date and forecast name. For each feature group and the comprising features, I can see the contributions made by each across my forecast horizon.