Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

Fundamental raises $255 million Series A with a new take on big data analysis

Fundamental has built a new foundation model to solve an old problem: how to draw insights from the huge quantities of ...

Fundamental launches with $255M and an AI model optimized for tabular data

Artificial intelligence startup Fundamental Technologies Inc. launched today with $255 million in initial funding from a group of prominent investors. The company raised the bulk of the capital ...
AI Business

Startup Introduces 'Large Tabular Model' for Spreadsheet Data

The company's AI tool was built to make sense of structured data, an area where large language models struggle.
TMCnet

Fundamental Announces $255M in Funding and Publicly Launches its Most Powerful Large Tabular Model (LTM)

Fundamental, an AI company that has built its most powerful Large Tabular Model ("LTM") to drive predictions from enterprise data, announced today it is emerging from stealth with $255M in funding.

AI venture Fundamental secures $1.2bn valuation and Amazon deal

Start-up partners with AWS to sell AI model designed to interpret petabytes of tabular data in company databases ...

Are LTMs the next LLMs? This new type of AI can do what large-language models can’t

Fundamental, which just closed a $225 million funding round, develops ‘large tabular models’ for structured data like tables and spreadsheets. Large-language models (LLMs) have taken the world by ...
Verdict on MSN

AI start-up Fundamental launches NEXUS, raises $255m in funding

The funding will be used to scale computing, enhance enterprise deployments, and expand research, engineering, and marketing teams.

From Text To Tables: Why Structured Data Is AI’s Next $600 Billion Frontier

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of structured, siloed, and confidential data.