Predictive Analytics & Decision Intelligence
We build forecasting, propensity, optimization and what-if simulation systems, with causal validation, explainability and the operational discipline that turns predictions into automated decisions.
Predictions are easy. Trustworthy decisions are not.
Anyone can fit a model. The hard part is the decision system around it: the feature store that does not skew, the eval harness that catches drift, the explainability layer that satisfies the audit committee and the causal validation that proves you are actually moving the metric. We build those four layers as deliberately as we build the model itself, because in production they matter more.
Causal proof, not correlational hope
Every recommendation is validated by uplift, A/B or synthetic control. We do not confuse "predicted to churn" with "would have churned but for our intervention".
Explainable by default
SHAP, counterfactuals and natural-language explanations baked into every prediction. Auditors, regulators and skeptical operators all get answers, not deflection.
Decisions, not just dashboards
Models are wired into operating systems (CRM, OMS, marketing platforms) as APIs, not just dropped into a quarterly slide. Predictions become actions, automatically.
Why predictive analytics is the highest-ROI AI investment in 2026.
Three economic shifts are pushing predictive analytics ahead of GenAI in the boardroom ROI conversation.
Forecasting, pricing and routing remain the highest-ROI AI levers in mature industries. The math has not changed; the tools have improved dramatically.
Decision intelligence as a category is growing faster than CRM did at the same stage. The teams investing now will own the next decade of operating efficiency.
That is the gap. The companies that close it, turning charts into recommendations, get a measurable, durable advantage.
Predictive Analytics services we offer.
Each item below is a discrete, measurable workstream we own end-to-end, with senior engineers, real timelinesand the test coverage to back it up.
Demand and revenue forecasting
Hierarchical, probabilistic, hybrid (statistical + ML) models with reconciliation across SKU/store/region. Accuracy lifts of 15-40% over incumbent vendors, audited.
Propensity and churn modelling
Per-customer scores for buy, churn, upgrade, lifetime value, with uplift validation so you target who is incrementally moveable, not just who is likely.
Optimization and operations research
MIP, LP and CP-SAT solvers for routing, scheduling, pricing and capacity, integrated with forecasting models so plans optimize against the right uncertainty.
What-if simulation and scenario planning
Counterfactual simulators on production data. Stress-test pricing, marketing spend, supply chain or staffing in seconds, before committing the budget.
Causal inference for business impact
Uplift modelling, difference-in-differences, synthetic controls and observational A/B for cases where randomized tests are not possible.
Real-time decisioning APIs
Sub-100ms scoring endpoints for fraud, pricing, recommendation and routing. Models served as APIs, with feature stores and drift monitoring built in.
We're fluent in your stack.
Vendor-agnostic by design. We pick the right tool for the problem in front of us, not the one our partner discounts apply to.
Real engagements. Real numbers.
Forecast accuracy +38%, working capital -19%
Hierarchical reconciliation plus weather, calendar and promo covariates across 12,000 SKUs. Stockouts and over-stocks both fell, working capital with them.
Six reasons enterprises run Predictive Analytics with Infivit.
Built for the 2026 reality of Predictive Analytics: the actual buyer pain, the actual technical constraints and the actual outcomes that matter, not generic data buzzwords.
Every prediction paired with a recommended action.
Reports tell you what happened. Our analytics tell you what to do next, with confidence intervals and expected lift attached to every recommendation.
Forecasts 25%+ more accurate than ARIMA.
Hierarchical, hybrid, probabilistic ensembles tuned for your seasonality, trend and shocks. Hospital-grade math, plain-English outputs.
Uplift, DiD, synthetic controls, A/B.
Stop confusing correlation with cause. Statistically valid answers to "what if we changed X?" before you change X, not after.
50 scenarios simulated in seconds.
Counterfactual simulators on production data. Stress-test pricing, marketing spend, supply chain or staffing in real time, before committing the budget.
SHAP, counterfactuals, audit-ready.
Every prediction comes with a one-paragraph explanation an auditor or operator can read. No black-box deflection in any room, ever.
Predictions to apps in under 100ms.
Models served as APIs, not just nightly batch to a spreadsheet. Decisions happen at the speed of the business, never at the speed of the dashboard refresh.
The questions you were already going to ask.
Got a predictive analytics problem?
Let's ship the fix.
A 30-minute call with one of our senior engineers, no slideware, no scoping doc. You leave with a concrete view of what the first 30 days look like.