Financial Forecaster

To forecast revenue and expenses, the Skill models historical financial time series by detecting trends and seasonality, then projects them into monthly, quarterly, or annual projections. It generates structured outputs across best, base, and worst-case scenarios.

Yes, you can calculate burn rate and runway by providing past monthly actuals. The Skill processes historical financial time series to project cash burn and estimate runway timelines under different growth and churn assumptions.

You build scenario analysis by applying adjustable assumptions to historical data, creating best, base, and worst-case projections. This models how runway timelines and break-even points shift under varying growth, churn, and expense planning conditions.

Yes, the forecasting approach supports cohort-aware revenue drivers and unit economics. It models churn, burn, and rate-based metrics from historical time series to calculate growth and explain variances between actuals and forecasts.

The best way to explain variance is by comparing actuals against the generated base, best, or worst-case forecasts. The Skill calculates growth rate and unit economics while explicitly stating the assumptions and uncertainty behind the projections.

You need at least 12 months of monthly historical actuals to project next quarter's revenue. This time series data allows the Skill to detect seasonal and cyclical patterns, extending them into future period forecasts.