Launching today
RootCause.ai
Causal Inference at Enterprise Scale
1 follower
Causal Inference at Enterprise Scale
1 follower
Most teams do causal inference 4-5 times a year. Each analysis is a bespoke project: specialized talent, months of work, results scoped to one question. Everything else runs on dashboards and intuition. RootCause.ai automates the full causal pipeline on observational data. Models built in minutes (Digital Twins). No experiments required. It discovers causal structure, recovers hidden confounders, and builds a digital twin you can simulate interventions against.
Hey Product Hunt 👋 I'm Ibrahim, Founding Marketing Director of RootCause.ai.
Here's the problem we built this to solve: causal inference is the best tool enterprises have for figuring out what actually works, but most teams can only afford to do it 4-5 times a year. Each analysis is a bespoke project requiring specialized talent and months of manual modeling. Every other decision gets made on dashboards and gut feel.
We automated the full causal pipeline on observational data. Connect your data sources, and the platform discovers the causal structure of your system, identifies hidden variables that would bias your estimates, and builds a digital twin you can simulate interventions against. Models that used to take months now build in minutes.
Built for insurance, logistics, financial services, telecom, and anywhere running a controlled experiment isn't an option but acting on a wrong assumption is expensive.
Would love your feedback. Happy to answer any questions about the tech or the use cases.