What is likely to happen?
Forecast demand, revenue, risk, customer value or another outcome early enough to act.
Decision Intelligence
Decision intelligence that ends with a business action.
Graphite Note helps companies move from what happened to what will happen, why it will happen, and what to change. It combines predictive models, causal analysis and optimisation around a specific commercial or operational decision.
What it means
From dashboards to interventions.
Business intelligence is valuable for monitoring performance. Decision intelligence starts where reporting stops: with a choice that can change an outcome.
A decision-intelligence system should connect the signal, forecast likely outcomes, test which drivers matter, compare feasible interventions and deliver a recommendation with evidence.
What is actually driving it?
Use causal methods where appropriate to separate actionable drivers from misleading correlations.
What should change?
Compare feasible actions and estimate the expected impact of each one.
How does the decision reach the workflow?
Deliver the recommendation through a business process, application or API and measure what changed.
Decision Intelligence vs BI
Reporting answers a different question.
Graphite Note is designed to complement existing BI, data warehouses and operational systems rather than reproduce them.
Read the full Decision Intelligence vs BI comparison
What happened?
- Dashboards and KPIs
- Descriptive trends
- Monitoring and reporting
- Human interpretation of the next move
What should we do?
- Prediction and uncertainty
- Causal evidence where needed
- Intervention comparison
- Recommended action and expected impact
Typical decisions
Use the model where a real choice exists.
Demand
How much will we need, and where?
Forecast future demand at the level where supply, stock or operations actually make decisions.
CustomersWho should we target first?
Score customers or leads and prioritise the opportunities with the strongest expected value.
OperationsWhich process change will move the KPI?
Move from correlated drivers to a ranked intervention plan backed by causal evidence.
Direct answers
Questions people ask about Decision Intelligence.
Is Decision Intelligence the same as AutoML?
No. AutoML automates parts of model development. Decision Intelligence is broader: it connects models to a business decision, constraints, interventions, evidence and action. See how AutoML fits.
Does Decision Intelligence replace Power BI or another BI tool?
Usually not. BI remains useful for monitoring and reporting. Graphite Note adds the predictive, causal and decision layer when the team needs to determine what happens next and what action to take.
What data does Graphite Note need?
It depends on the decision. A useful starting point is historical outcome data plus the operational, customer, commercial or external variables that may affect that outcome. We scope data requirements around the decision rather than around a generic platform checklist.
Explore the stack
The capabilities behind the decision.
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.
Industries
See Decision Intelligence in a specific operating context.
RetailDemand, customer value, targeting and store-level planning.eCommerceBasket analysis, product affinity, customer value, targeting and demand.CPG & BeveragesDemand drivers, distribution, promotions and commercial interventions.ManufacturingQuality, scrap, process drivers and operational interventions.HospitalityGuest segmentation, audience value and commercial targeting.TelecommunicationsLead scoring, churn, cross-sell and customer prioritisation.
Bring us the decision your team cannot resolve.
We will show you what the data can prove, what it cannot, and where a model can change the outcome.