Advanced Analytics & Decision Science
We build the analytics layer that closes the loop between data and decision, forecasting, optimization, causal inference and uplift models that move P&L lines, not just dashboards.
Analytics that ends in a decision, not a chart.
Most analytics projects deliver a dashboard and call the work done. We think that's where the work starts. Our approach is to ship analytics products: forecasting, optimization and causal models embedded in the workflow that changes a decision. Every engagement ends with an artifact a business owner uses on Monday morning and a measurable lift on the metric we said we'd move.
Recommend, don't just describe
Outputs are recommended actions with expected uplift, not bar charts a decision-maker has to interpret.
Causal-first, not correlation-driven
A/B tests where possible, synthetic controls where not. We commit to lift, not vibes.
Operational, not one-shot
Models live in your stack with retraining flows, drift monitors and an owner, not in a one-time PowerPoint.
Why analytics is the unsexy AI investment that pays back fastest.
GenAI gets the headlines. Forecasting and optimization quietly print the money. The teams that double down on decision science are compounding faster than the ones chasing model-of-the-week.
Analytics 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.
Routing, pricing, inventory and capacity are the unsexy levers that move billion-dollar P&Ls. Our customers see it consistently.
That's the gap. The companies that close it, turning charts into recommendations, get a measurable, durable advantage.
Advanced 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 & revenue forecasting
Hierarchical, probabilistic forecasts at SKU × store × day granularity, with uncertainty intervals planners actually trust.
Operations research & optimization
Routing, scheduling, inventory, pricing, formulated as MIP/LP/CP-SAT and solved at production scale (CBC, Gurobi, OR-Tools).
Causal inference & experimentation
A/B testing platforms, switchback experiments, synthetic controls and double-ML, measuring lift on top of pre-existing trends, not noisy correlations.
Churn, propensity & uplift modeling
Beyond churn-prediction: which intervention works for which customer? Uplift models target spend where it changes outcomes.
Recommender systems
Two-tower retrieval + transformer rerankers, cold-start handling and exposure bias controls, tuned for revenue, not click-through.
Decision dashboards
Streamlit / Dash / dbt-Looker stacks that show recommended actions, the data they're based onand the expected uplift, not just charts.
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.
Inventory optimization across 1,200 stores
Hierarchical forecasting + a MIP-based replenishment optimizer cut stockouts 31% while bringing inventory carrying cost down 18%.
Six reasons enterprises run Advanced Analytics with Infivit.
Built for the 2026 reality of Advanced Analytics: the actual buyer pain, the actual technical constraints and the actual outcomes that matter, not generic AI talking points.
Every chart 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 and probabilistic ensembles tuned for your seasonality, trend and shocks. Hospital-grade math, plain-English outputs.
Uplift, DiD, synthetic controls, A/B at scale.
Stop confusing correlation with cause. We give you statistically valid answers to "what if we changed X?" before you change X, not after.
50 scenarios simulated in seconds.
Counterfactual simulators built on your data. Stress-test pricing, marketing spend, supply chain, or staffing in real time, before betting the budget on it.
Natural-language queries on a semantic layer.
Business users ask in English, the governed semantic layer translates to SQL. The 200-line ticket queue to the analytics team becomes a memory.
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, not the speed of the dashboard refresh.
The questions you were already going to ask.
Got a advanced 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.