> ## Documentation Index > Fetch the complete documentation index at: https://kumo.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # Overview > Introduction to KumoRFM — the relational foundation model for predictive AI on relational data [Kumo](https://kumo.ai/) is a next-generation predictive AI platform for relational data that lets you generate high-quality predictions directly from your data warehouse without model training or feature engineering. At its core is [KumoRFM](https://kumo.ai/research/kumo_relational_foundation_model.pdf), a **relational foundation model** trained on large-scale real and synthetic relational data that performs in-context predictions. It learns from your existing data at query time without training, enabling fast, production-ready predictions with minimal setup. For use cases that require additional optimization, KumoRFM can also be **fine-tuned** for task-specific performance. Prediction tasks are defined using **Predictive Query Language (PQL)**, a lightweight SQL-like interface. **Kumo's coding agent** translates natural language into PQL and helps you author and iterate on SDK-based workflows directly in your notebook or IDE of choice. The KumoRFM SDK supports two modes: For instant, in-context predictions. No model training required. For optimizing performance on specific tasks with custom training. AI agent that translates natural language into PQL and SDK workflows. ## Get Started Open in Google Colab Open in Google Colab