![Inna Tokarev Sela Inna Tokarev Sela](https://pic1.calcalist.co.il/picserver3/crop_images/2024/06/27/S1KzfjcIC/S1KzfjcIC_0_0_2001_1635_0_large.jpg)
Illumex raises $13 million Seed round for enterprise GenAI platform
Illumex raises $13 million Seed round for enterprise GenAI platform
The platform acts as an intermediate layer that reconciles data silos and automatically adds context and meaning to data
Illumex, which has developed a Generative Semantic Fabric platform for structured enterprise data, announced on Thursday that it has raised $13 million in Seed funding. The round was led by Cardumen Capital, Amdocs Ventures, and Samsung Ventures, with participation from ICI Fund, Jibe Ventures, Iron Nation Fund, Ginnosar Ventures, ICON Fund, Today Ventures, and angel investors.
Illumex helps organizations to overcome data challenges that hinder generative AI (GenAI) initiatives by automating the creation of a semantic layer that unifies data silos and adds business context, as well as generating a consistent vocabulary of domain-specific terminology. Illumex, an alumni of the Intel Ignite and ICON programs, already has clients of the likes of Teva and Carson using its platform. The company employs 15 people, with a majority of female employees.
"The key to enterprise generative AI success lies in solving the fundamental data challenges that have caused so many projects to fail," said Inna Tokarev Sela, Founder and CEO of illumex. Tokarev Sela is a former AVP & Head of AI at Sisense and Senior Director of Machine Learning at SAP.
Illumex's platform analyzes metadata — without accessing the underlying sensitive information — to create a unified semantic knowledge graph. This graph acts as a single source of truth that aligns all data with consistent business terminology and context. This serves as a foundation that enables LLMs to reliably map user questions to the relevant data points that should be retrieved in order to deliver accurate results while ensuring proper governance.
"Our Generative Semantic Fabric aligns organizational data with business meaning and domain-specific context, allowing organizations to finally trust the results of their AI initiatives. By enabling business users to interact reliably with data using natural language, without teaching them the precise technical definitions, we're democratizing AI and empowering enterprises to make better decisions," added Tokarev Sela.