Who is Rabble?

We kept watching the same thing happen.

A team spins up an ambitious AI project. The demo works. Then it meets the real data, thirty years of it, scattered across systems that were never built to talk to each other, let alone talk to an agent. The project stalls. Everyone blames the model.

It was never the model. It was the data underneath it.

We learned this the hard way. Rabble started out helping SaaS companies understand customer behavior,  ingesting product and operational data, running ML models to surface hidden signals like churn risk and upsell opportunities. It worked. Until it met real enterprise data, and we spent more time cleaning and contextualizing that data than we did on anything else. When we started adding GenAI capabilities, the problem got louder: if data wasn't ready for traditional ML, it had no shot with autonomous AI agents.

So we stopped fighting the symptom and went after the cause.
Rabble exists to fix the layer nobody wants to touch, the messy, legacy, business-critical data that AI has to understand before it can do anything useful. We've spent our careers in that layer.

Hence, Rabble was born. Again.