The challenge
Analysts were producing forecasts with spreadsheet models that took a long time to update and were hard to audit, which slowed down planning and risk reviews.
What we built
We built a forecasting system around time-series models, with a pipeline that refreshes predictions as new data arrives and an interface that shows forecasts, confidence ranges and risk indicators side by side.
Market forecasting
Time-series models that project key indicators forward with confidence ranges rather than single-point guesses.
Risk assessment
Scenario views and risk indicators that help teams understand exposure before it becomes a problem.
Automated data pipeline
Scheduled ingestion and model refresh, replacing manual spreadsheet updates with repeatable, auditable runs.