Basic raises $255 million in Series A for new take on big data analytics
An AI lab called Fundamental came out of hiding on Thursday, offering a new foundational model to solve an old problem: how to find insights from the vast amounts of structured data generated by businesses. By combining old predictive AI systems with modern tools, the company believes it can reshape the way large enterprises analyze their data.
“While LLMs work well with unstructured data, like text, audio, video, and code, they don’t work well with structured data like tables,” CEO Jeremy Fraenkel told TechCrunch. “With our Nexus model, we’ve built the best base model for handling that kind of data.”
The idea has already attracted a lot of interest from investors. The company is coming out of the IPO with $255 million in funding at a $1.2 billion valuation. Most of it comes from a recent $225 million Series A round led by Oak HC/FT, Valor Equity Partners, Battery Ventures, and Salesforce Ventures; Hetz Ventures also participated in Series A, with angel funding from Perplexity CEO Aravind Srinivas, Brex founder Henrique Dubugras, and Datadog CEO Olivier Pomel.
Called the Large Table Model (LTM) rather than the Large Language Model (LLM), Fundamental’s Nexus departs from modern AI practices in several important ways. The model is deterministic – that is, it will give the same answer every time it is asked a given question – and does not rely on the transformer design that defines models from many modern AI labs. Fundamental calls it a basic model because it goes through the usual steps of pre-training and fine-tuning, but the result is something very different from what a client would get when working with OpenAI or Anthropic.
That distinction is important because Fundamental is a rush to use where modern AI models often falter. Because Transformer-based AI models can only process data within their context window, they often have trouble thinking about very large datasets — analyzing a spreadsheet with billions of rows, for example. But that kind of massive structured dataset is common among large enterprises, creating a significant opportunity for models that can handle scale.
As Frankel sees it, that’s a huge opportunity for Fundamental. Using Nexus, the company can bring modern techniques to Big Data analysis, offering something more powerful and flexible than the algorithms currently used.
“Now you can have one model for all of your use cases, so you can now dramatically increase the number of use cases,” he told TechCrunch. “And for every use case, you get better performance than you could with an army of data scientists.”
That promise has already resulted in a number of high-profile contracts, including seven contracts with Fortune 100 customers. The company has also entered into a strategic partnership with AWS that will allow AWS users to use Nexus directly in existing environments.
