Ontology
It learns your business, not just your tables.
Connect spreadsheets, databases, documents and data warehouses. RootCause.ai resolves entities, time, location and meaning without a bespoke pipeline.
A causal model of your business. In one shot.
RootCause.ai is an enterprise data unification and decision intelligence platform. It maps your fragmented data into a business ontology, discovers the cause-and-effect relationships inside it, and builds a causal digital twin you can simulate against before you commit.
OntologyCausal modelSimulation
Causal inference, for everyone.
Decades of causal science sat with big tech, in-house data teams, and long consulting engagements. RootCause.ai packages it into one repeatable platform. Thousands of causal models in parallel, built in hours. Specialists used to manage only a handful a year.
Fragmented data in. A queryable causal model out.
RootCause.ai compresses a months-long specialist workflow into one autonomous system.
Causal Model
Generate the model. Inspect every edge.
RootCause.ai searches the causal structure, quantifies confidence and exposes the evidence behind every relationship. Nothing is asserted that you cannot trace back to the data. The result is a temporal digital twin you can interrogate.
Simulation engine
Ask what happens before you act.
Run interventions, counterfactuals, forecasts and optimizations through the same underlying model. Use it directly, or expose it through API and MCP.
Conventional discovery
O(n²)
RootCause.ai
O(n log n)
volume of data (GB)→
time to result→
Causal AI Scaled.
What this looks like in production.
Four deployments, four different questions, and what the causal model found in each.
20% → 5%Forecast error
Market and operational levers mapped into forecasts that planning teams can use. Built in one week against an estimated 1.5 years to build internally.
- Demand Forecasting
- Churn Prevention
- Marketing ROI
95%Less analysis effort
KPI root cause that took two analysts three to four days per KPI per market, run automatically across 142 KPIs and 42 markets.
- KPI Root Cause
- Performance Drift
€30MAnnual savings potential
Demand, shrink and pricing connected to the decisions that move them, including the feedback loop where a stockout compounds losses that never get attributed back to it.
- Pricing
- Shrink
- Demand
$500KSavings per 1,000 vehicles
12,000 incidents and 10GB of telematics. The real driver was minutes since last rest break. Not speed, not weather, not location. Found in one hour.
- Safety
- Fleet Optimization
Use cases
20% → 5%Forecast error
Market and operational levers mapped into forecasts that planning teams can use. Built in one week against an estimated 1.5 years to build internally.
- Demand Forecasting
- Churn Prevention
- Marketing ROI
95%Less analysis effort
KPI root cause that took two analysts three to four days per KPI per market, run automatically across 142 KPIs and 42 markets.
- KPI Root Cause
- Performance Drift
€30MAnnual savings potential
Demand, shrink and pricing connected to the decisions that move them, including the feedback loop where a stockout compounds losses that never get attributed back to it.
- Pricing
- Shrink
- Demand
$500KSavings per 1,000 vehicles
12,000 incidents and 10GB of telematics. The real driver was minutes since last rest break. Not speed, not weather, not location. Found in one hour.
- Safety
- Fleet Optimization
Built for the questions procurement will ask.
A platform engineered for security, usability, and transparency. Built for regulated industries.
Your data never leaves your organisation.
RootCause.ai runs inside your own environment.
Connect to how you already work.
API, SDK, and MCP support so the model plugs into your stack.
Every answer is traceable to its source.
No black box. Trace the answers back to the data.
See exactly what matters. Control what happens next.
Bring a high-value question and the data around it. We will show you the causal model behind the answer.
Book a Demo
A 30-minute walkthrough with a causal AI engineer, not a sales deck. Bring one real question and we will show you how the model gets to the answer. We reply within one business day.