Introduction
Coming soon: KumoRFM as an NVIDIA NIM container
This documentation is still being updated ahead of the public release. Please stay tuned.
KumoRFM is a pre-trained relational foundation model that generates high-quality predictions directly from your data — no training required. It learns from your existing relational data at query time using in-context learning, enabling fast, production-ready predictions with minimal setup.
Prediction tasks are defined using Predictive Query Language (PQL), a lightweight SQL-like interface. You can also use the Kumo Coding Agent to translate natural language into PQL and iterate on workflows directly in your IDE.
The KumoRFM SDK workflow follows these steps:
Install the SDK, authenticate, and connect to your data sources.
Configure your notebook or editor environment for agent-assisted work.
Load tables, define data types, and build a relational graph.
Write PQL queries and generate instant predictions.
Evaluate prediction quality and understand what drives results.