Anticipate quality or throughput risk
Use production history and relevant process signals to identify where an outcome is likely to deteriorate.
Manufacturing Decision Intelligence
Know which process change is worth making first.
Graphite Note helps manufacturing teams move beyond monitoring scrap, quality or throughput to identifying which controllable drivers matter and which intervention should be prioritised.
From signal to intervention
Operational data becomes useful when it changes the process.
Separate real drivers from correlation
Use causal methods when the decision is about changing tool intervals, material tolerance, temperature or another controllable variable.
Rank feasible process changes
Combine expected effect with feasibility and operating constraints to define the next move.
Evidence
Dashboards said where scrap rose. Causal analysis identified what to change.
In one manufacturing case, the objective was not to predict scrap for its own sake. The team needed to determine which of several correlated process variables were credible intervention levers.
The result was a ranked action plan tied to measurable operational outcomes.
Read the full case studyMeasured outcome
4.1% → 2.2% scrap rate
The published case study reports a 1.9 percentage-point reduction in six months and more than €1.4M annualised cost recovery.
Decision IntelligenceFrom signal and prediction to a governed business action.AutoMLAutomate repetitive model-building work without losing business context.Causal Machine LearningSeparate drivers from correlations and estimate intervention effects.Predictive AnalyticsForecast demand, score customers and anticipate business outcomes.Decision OptimisationCompare feasible actions and rank them by expected business impact.Decision APIDeliver recommendations, expected impact and evidence into workflows.Embedded Decision IntelligenceAdd a decision layer to ERP, CRM, BI, workflow and vertical software.Build vs BuyA practical framework for deciding whether to build, buy or embed.
Bring the KPI and the process variables you can actually change.
We will help determine whether the data can support a credible intervention plan.