A new French artificial intelligence company is betting that the future of AI isn’t just about processing text and images, but rather in handling the mundane yet crucial world of structured business data.
Neuralk-AI announced $4 million in seed funding led by Fly Ventures, with participation from SteamAI and notable tech industry figures, to develop specialized AI models focused on tabular data analysis. The investment comes as companies increasingly seek ways to leverage their existing data warehouses and lakes more effectively.
“The real value for companies lies in data that was identified long ago, structured in tables, and used by data scientists to create their machine learning algorithms,” says Alexandre Pasquiou, co-founder and Chief Scientist Officer at Neuralk-AI.
While large language models have garnered attention for their ability to process unstructured data, they remain expensive to access and operate. Neuralk-AI aims to fill a gap in the market by focusing specifically on structured data applications, particularly in the retail sector where product catalogs, customer databases, and shopping trends form the backbone of operations.
The company plans to initially offer its technology through an API targeting data scientists in commerce companies. Early applications include automated data deduplication, fraud detection, product recommendation optimization, and sales forecasting for inventory and pricing decisions.
Several prominent French retailers and commerce startups, including E.Leclerc, Auchan, Mirakl, and Lucky Cart, have signed on as early testing partners. The company expects to release its first model and public benchmarks within three to four months.
The funding round attracted notable individual investors from the French tech ecosystem, including Hugging Face’s Thomas Wolf, Alan’s Charles Gorintin, and Mirakl’s Philippe Corrot and Nagi Letaifa.
“By September, we aim to establish ourselves as the leading tabular foundation model in representation learning,” Pasquiou says, highlighting the company’s ambitious goals in this specialized AI segment.
The investment underscores growing interest in AI applications that can handle structured data more efficiently than current large language models, potentially offering businesses a more cost-effective way to leverage their existing data infrastructure.