Simulations for Enterprise Decisions

Every Decision Backed by Causal Inference

Most analytics tools report the past. RootCause AI helps you simulate the future. Using a causal AI digital twin built from your enterprise data, you can run what-if analysis, test scenarios, and compare outcomes across revenue, cost, churn, marketing, product, and operations before committing to a decision. The result is forward-looking, data-backed strategy, not guesswork.

Interventions

What-If Analysis & Scenario Simulation

Test 'what-if' scenarios by manually changing variable values and measuring their impact on your business metrics. Perfect for policy decisions and strategic planning.

Example questions:

  • What happens to churn if I give away free tech support?
  • What happens to sales if I increase ad spend?
  • What happens to engagement if I add email reminders?

Optimizations

Best Action Recommendations

Automatically find the best variable settings to maximize or minimize your objectives while respecting constraints. Ideal for resource allocation and strategy optimization.

Example questions:

  • How can I maximize bookings using price and schedule changes?
  • Where should I intervene to lower unit cost fastest?
  • What's the best way to increase batch yield in production?

Counterfactuals

Alternate Outcomes & Next Steps

Find the minimum changes needed to achieve a desired outcome. Automatically discovers the most efficient path to your target goals.

Example questions:

  • Which supplier, route, or timing should I change to improve delivery times?
  • Should a nurse be assigned to this claim to reduce claim costs?
  • What care change should I make for each patient to reduce readmissions?

Explanations

Root Cause Insights

Uncover the root causes behind outcomes. Discover what drives your key metrics and understand the full impact of your decisions.

Example questions:

  • What's causing sales to increase when it rains?
  • What's increasing delays from SFO?
  • What's driving shrinkage after 6pm?

Predictions

Forward-Looking Estimates

Forecast future outcomes with confidence intervals. Use current data to predict what will happen next and assess risks.

Example questions:

  • What is projected drug demand by region?
  • Which of these claims will exceed $50K?
  • How many of these shipments will be delayed?

Forecasts (Temporal Models)

Time-Based Outcome Forecasting

Generate time-based forecasts with uncertainty for temporal twins.

Example questions:

  • How will hospital admissions change as the temperature rises?
  • How will delivery delays change if fuel costs increase?
  • What will happen to claim costs if treatment costs rise?

Temporal Interventions

Sequenced Decision Simulation

Script time-based policies by changing variables over time and measuring impact on your metrics.

Example questions:

  • What happens to online sales if I stop advertising after Thanksgiving?
  • What happens if vehicle downtime increases in the winter?
  • How will productivity change if training starts in Q1 vs Q2?

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