ForecastingKnow in March what most companies learn in June
Cash, revenue, and demand projected forward with honest uncertainty. See problems while they're still cheap to fix.
Forecasting is where analytics starts paying for itself. Cash runway, revenue trajectory, demand, and risk, quantified with honest ranges instead of gut feel. The point isn't predicting the future perfectly. It's making better decisions today, while the options are still open.
We build forecasting systems that retrain on your live data and present results in language operators understand. We build this for ourselves too: Aegis BI, live in production, forecasts cash and revenue with scenario modeling, and MyBudgetNerd, live on the App Store, forecasts personal spending with anomaly detection.
Cash and revenue projections live in a spreadsheet updated quarterly, if at all
Plans rest on last year's seasonality, and nobody measures forecast error
Unusual transactions and cost drift get caught months late
"What happens if we hire two more people?" takes a week of analyst time to answer
A Worked Example
Two shipped forecasting systems
Cash and revenue projection with honest uncertainty in Aegis BI, retrained as new data arrives; spending-trajectory forecasts and statistical anomaly detection in MyBudgetNerd, live on the App Store. Both are written up, including where the models are weak.
Go and lookTwo ways in: a 2–3 week fixed-scope diagnostic on whether your data can support a forecast worth trusting, or 4–6 weeks to a model in production with its uncertainty stated honestly. Most start with the diagnostic.
Forward-looking by default
Runway, trajectory, and risk quantified continuously, not reconstructed after the quarter closes.
What-if in minutes
Model hiring, pricing, and spend decisions on the spot instead of waiting a week for analysis.
Problems caught early
Statistical anomaly detection flags unusual movement while correcting it is still cheap.
Related Work
Aegis BI
AI-assisted financial intelligence that stays current: connect OneDrive or Google Sheets, then read the numbers anywhere through command-center dashboards, forecasting, what-if scenarios, and the Glaukos AI analyst.
Flagship · App Store
MyBudgetNerd
A shipped consumer finance product: PDF statement parsing, ML transaction categorization, and the Oracle engine for anomalies, category outlook, and plain-language explanation.
iOS · App Store
Aegis BI: Building an AI Financial Command Center for Small Business
How we designed and built a BI platform that reads the files a business already keeps, forecasts from them, and travels in a pocket, now live in production.
4 min read
MyBudgetNerd: Shipping Privacy-First ML Personal Finance to the App Store
From PDF parsing pipeline to 5.0-star iOS app: designing, building, and shipping a consumer ML product with privacy as the architecture, not the disclaimer.
2 min read
Practical Forecasting for Small-Business Finance
You don't need a data science team to forecast cash and revenue. You need clean history, honest uncertainty, and models you can explain to whoever bets on them.
2 min read
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