Transparency over mystery
We publish assumptions, drivers, and limitations so the forecast can be challenged and improved.
Forecasting systems that respect reality
CKO Forecasting AI is a specialist practice focused on operational forecasting. We help planning teams move from fragile spreadsheets and one-off experiments to a stable forecasting system: data checks, baselines, model selection, deployment, and monitoring. Our work is designed to be adopted by the people who plan every day, not only by data scientists.
Partnership
We co-design with planners and operations.
Governance
Clear limits, reviews, and accountability.
A quick view of our focus
What we optimize
Accuracy, bias, and stability, tied to service levels and cost.
What we avoid
Black-box forecasting without baselines, monitoring, or clear ownership.
What you receive
A working pipeline, documented methods, and an enablement plan.
🌐 How it looks
Dashboards are built for planners: segment views, explainability, and health checks.
Our principles
AI forecasting is most valuable when it is understood, monitored, and integrated into decision-making. We use methods that are rigorous but practical and we document tradeoffs clearly.
Stability across time
We measure drift and performance decay, with retraining rules and clear release cycles.
Planner control
Overrides, notes, and approvals are part of the system so expertise stays in the loop.
Privacy by default
We minimize data, define access rules, and document retention and purpose limitations.
How we work with your team
We start by mapping decisions: what gets ordered, staffed, or scheduled, and when. Then we define horizons, aggregation levels, and what “good” looks like using your business metrics. During delivery, we keep a predictable cadence of demos and reviews so stakeholders see progress and can steer priorities early. At handover, we provide operating guidance, monitoring thresholds, and a clear owner checklist.
Operating checklist
- Daily data quality rules and missing value alerts
- Weekly accuracy review by segment and horizon
- Monthly bias and override analysis for governance
- Quarterly retraining decision with documented reasons
Need a starting point? Read our practical guides in Insights.