Workflow

RootCause.ai transforms your data into actionable causal insights through four main stages:

Connect Data → Build Ontology → Discover Causes → Simulate

1. Connect Data

Import your data from files, databases, or APIs. RootCause.ai supports a wide range of data connectors including PostgreSQL, Snowflake, S3, and more. Whether your data lives in spreadsheets, data warehouses, or operational systems, you can bring it together in one place.

2. Build Ontology

The Ontology organizes your data by identifying entities, time, and location. This creates a unified view across disparate datasets and ensures consistent analysis. Think of it as teaching RootCause.ai the structure of your business: what a "customer" is, what "revenue" means, how different data sources relate.

3. Discover Causes

Causal Discovery automatically identifies cause-and-effect relationships in your data, producing a causal graph that distinguishes true drivers from mere correlations. This is where RootCause.ai does the heavy lifting—analyzing thousands of potential relationships to find the ones that matter.

4. Simulate

The Digital Twin lets you test interventions, explore counterfactuals, and optimize decisions before acting in the real world. Ask "what if" questions and get answers backed by causal evidence, not just historical patterns.