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.
The Graphite Note decision stack
Prediction. Causal evidence. Optimisation.
Each capability answers a different part of the same business decision. Use them independently when that is enough, or connect them when the decision requires the full chain.
Predictive analytics
What is likely to happen?
Forecast demand, revenue, churn, risk or value at the level where the business can still act.
Causal AI & causal MLWhat can actually change it?
Estimate intervention effects and distinguish actionable drivers from correlation when the decision is about changing an outcome.
OptimisationWhich feasible action should we choose?
Compare expected outcomes under budget, capacity, stock, policy or other operating constraints.
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 or compare Decision Intelligence vs AutoML.
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. See Decision Intelligence vs BI.
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.
What is a GN Decision Pack?
A GN Decision Pack packages a recurring industry decision around a reusable workflow: the relevant data, modelling pattern, business constraints and action output. The same Graphite Note decision engine sits underneath each pack.
Are GN Decision Packs fully prebuilt products?
They are prebuilt where the decision pattern repeats and configured where each business is different. Graphite Note reuses decision workflows, model patterns, evaluation methods and output structures, then configures objectives, interventions, constraints and data mapping around the customer.
What comes out of a Decision Pack?
The target output is not only a score or dashboard. It is a business-ready recommendation such as a forecast, prioritised audience, intervention, allocation or next-best action with evidence and expected impact.
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.Forecasting vs OptimisationSee where prediction ends and the business decision begins.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.
GN Decision Packs
One decision engine. Six repeatable decision products.
The horizontal technology stays consistent: predictive analytics, causal evidence, optimisation and governed delivery. Each pack configures that engine around the recurring decisions, data and constraints of a specific operating context.
Decision PackRetail
Which SKUs should each store or channel carry, and where should stock or targeting change?
Models inside
AssortmentDemandPromotionInventory
Output
View Retail Pack →Recommended assortment, allocation and next action.
Decision PackeCommerce
What should we recommend, who should we retain, and which offers can move basket value?
Models inside
RecommendationChurnPricingPromotion
Output
View eCommerce Pack →Next best offer and action by customer segment.
Decision PackCPG & Beverages
Which prices, promotions and distribution moves will actually increase volume or margin?
Models inside
Price elasticityPromotionDemandDistribution
Output
View CPG & Beverages Pack →Recommended commercial move and expected impact.
Decision PackManufacturing
What should run, where and when under real machine, labour, material and capacity constraints?
Models inside
ForecastingSchedulingCapacityRoot cause
Output
View Manufacturing Pack →Optimised production plan and next operational action.
Decision PackHospitality
Demand changed. What pricing, offer, targeting or revenue action should we take now?
Models inside
Demand forecastPricingSegmentationOffer optimisation
Output
View Hospitality Pack →Recommended revenue action and expected impact.
Decision PackTelecommunications
Which churn-risk customer should receive which retention or next-best action?
Models inside
ChurnNext best actionSegmentationOffer optimisation
Output
View Telecommunications Pack →Recommended customer action and expected value.
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.