Fundamental emerges from stealth with $255M for structured data AI

An artificial intelligence lab called Fundamental emerged from stealth on Thursday, announcing $255 million in total funding at a $1.4 billion post-money valuation. The capital includes a $225 million Series A round. The funding will support the development of Nexus, the company’s foundation model designed to analyze structured data.

The Series A round was led by:

• Oak HC/FT
• Valor Equity Partners
• Battery Ventures
• Salesforce Ventures

Hetz Ventures also participated in the Series A round, alongside angel investors including Perplexity CEO Aravind Srinivas, Brex co-founder Henrique Dubugras, and Datadog CEO Olivier Pomel.

The company’s model, Nexus, is what it calls a large tabular model (LTM), representing a departure from standard large language models (LLMs). While LLMs are built to process unstructured data—information without a pre-defined format, such as text, audio, video, and code—Nexus is designed specifically for structured data, which is organized in formatted repositories like databases and spreadsheets. Unlike most contemporary AI models, Nexus is deterministic, meaning it produces the same output for a given input every time, and it does not rely on transformer architecture, the deep learning framework that powers most modern LLMs.

According to Fundamental, transformer-based models often struggle to reason over extremely large datasets, such as spreadsheets with billions of rows, because they can only process data within their context window. Fundamental’s model goes through pre-training and fine-tuning, but is designed to handle these massive structured datasets.

“While LLMs have been great at working with unstructured data, like text, audio, video, and code, they don’t work well with structured data like tables,” CEO Jeremy Fraenkel said. He stated that with Nexus, the company has built the best foundation model to handle structured data.

Fundamental has already secured contracts with Fortune 100 clients. The company has also established a strategic partnership with AWS, allowing users to deploy Nexus directly from existing instances. Fraenkel noted that the model allows enterprises to expand the number of use cases they can address, achieving better performance on each use case than what would otherwise be possible with an army of data scientists.

Why it matters

Fundamental is attempting to solve the structured data gap in current AI, moving beyond the text-heavy capabilities of LLMs to provide deterministic analysis for massive enterprise datasets.