Israeli startup Illumex is focused on getting an organization’s structured data involved in stopping GenAI chatbot hallucinations and has just received $13 million in a seed funding round to develop its software.
GenAI chatbots are large language models (LLMs) trained on general and unstructured information sources such as files, objects, images, audio, and so forth. They can produce incorrect responses when asked about topics on which they have not been specifically trained. RAG (retrieval-augmented generation) technology adds in an organization’s proprietary data into the mix so that the LLM can more correctly source and generate request responses. Until now, that has meant using unstructured data as the RAG source. Illumex wants to change that and bring structured (database) data into play as well, which is a logical step.
Founder and CEO Inna Tokarev Sela says her startup has developed a Generative Semantic Fabric (GSF): “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.”
Unstructured data has a lot of metadata associated with it – think file owner, type, creation date, length, etc. Structured data, such as a database record, has sparse metadata and no inherent context from which an LLM can deduce meaning, yet there is implied metadata, for example, in the record’s row and column address and its relationship with other row and column items.
The turnkey GSF software analyzes such metadata, without accessing the underlying sensitive information, to create a unified semantic knowledge graph. It works, Illumex says, “by automatically constructing a domain-specific ontology, which formally defines the entities, properties, and relationships that represent an organization’s knowledge structure.” GSF “automates the complex process of mapping data semantics and resolving terminological inconsistencies across business silos,” helping with information governance.
This graph aligns all data with consistent business terminology and context, and “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.” GSF is used to create, Illumex says, domain-specific Semantic AI engines that bring users a hallucination-free ChatGPT-like experience they can fully trust.
According to Sela: “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.”
Before founding Illumex, Sela was VP of AI at Sisense, spending just over two years there, and Senior Director of Machine Learning at SAP, where she worked for more than 11 years. She led the product and GTM for cloud and machine learning, built AI-driven platforms within the organizations, and established data science departments. Sela has authored several patents on knowledge graphs, natural language, and deep learning.
Illumex was founded in 2021, taking in $4.3 million in initial seed funding that year. Its second and latest seed round brings total funding to $17.3 million. 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 various angel investors.
The company says it has large enterprises like Teva and Carson using it for their data AI readiness, and has built agreements with Microsoft, Google Cloud, and AWS.
