Equitus KGNN is an automated data unification platform in the knowledge graph and AI data infrastructure category. It is designed for enterprise organizations seeking to ingest, structure, and contextualize large volumes of structured and unstructured data without relying on traditional ETL processes. KGNN automates the transformation of disparate enterprise data into semantically enriched, AI-ready knowledge to support use cases such as analytics, business intelligence (BI), and generative AI (GenAI) deployment. Equitus KGNN uses a combination of natural language processing (NLP), machine learning (ML), and semantic technologies to dynamically build a self-constructing RDF knowledge graph. This semantic core enables organizations to extract entities, relationships, and contextual meaning from raw data—including documents, logs, and databases, and transform it into structured, vectorized formats optimized for advanced analytics and AI model consumption.

KGNN

AI accuracy starts here

AI accuracy starts here