NEXUS is a foundation model developed by Fundamental and built for tabular data prediction. Large language models (LLMs) are designed for text, and traditional machine learning (ML) approaches require extensive feature engineering and model training. NEXUS takes a different approach. It’s pre-trained on billions of real-world prediction tasks across structured datasets, so it arrives already knowing how to find signal in your data.

As a Large Tabular Model, NEXUS is built for structured data analysis and offers these key innovations:

The most valuable enterprise data sits in tables such as spreadsheets, enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and relational databases. Many critical business decisions depend on predictions made against this data. However, today’s tools have significant limitations:

NEXUS is architected for tabular data and provides advantages such as the following: