Match the planning window
Build the forecast around when the team can still act.
Predictive Analytics
See the likely outcome early enough to do something about it.
Graphite Note builds predictive models for business planning, forecasting and prioritisation. The aim is not a model score in isolation. It is a prediction at the level where a team can actually make a decision.
Common patterns
Forecast. Score. Prioritise.
Forecasting
Demand and revenue
Estimate future demand or revenue with uncertainty at the store, product, region or business-unit level.
PropensityCustomer and lead scoring
Rank opportunities by likelihood or expected value so teams spend limited capacity where it matters.
ValueCustomer lifetime value
Estimate future value and retention risk for more disciplined acquisition and retention decisions.
Decision-ready forecasting
A forecast is useful when it changes a plan.
Graphite Note focuses on the operational unit, horizon and uncertainty that the business needs. A single top-line forecast may be accurate and still be useless if planners allocate people, inventory or budget at a much finer level.
Predict at the decision level
Store, brand, customer, region or another unit that maps to real execution.
Show confidence, not false precision
Expose uncertainty where it changes planning or risk tolerance.
Direct answers
Predictive analytics without the fog.
How is predictive analytics different from causal analytics?
Predictive analytics estimates what is likely to happen. Causal analytics asks what would change if an intervention changed. Both can be useful in the same decision workflow.
Can Graphite Note use external variables?
Yes, when they are relevant and available. External signals can improve forecasts if they carry information about the future outcome and are available at prediction time.
What happens after the forecast?
That depends on the business decision. The prediction can feed planning, prioritisation, a causal analysis, optimisation or a machine-readable recommendation through the Decision API.
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.
Build the forecast around the decision.
Start with the planning question, not the algorithm.