CollabNext, Retrieval Augmented Generation for Knowledge Graphs

CollabNext implements Retrieval Augmented Generation to reduce hallucinations from generative large language models. The solution summarizes only exact insights from the Knowledge Graph, ensuring accuracy in generated outputs. The system serves four universities: Georgia Tech, Morehouse College, Clark Atlanta University, and University of Buffalo.

Four universities benefit from this solution. By grounding LLM outputs in Knowledge Graph data, the system addresses the problem of AI hallucinations that can produce inaccurate or fabricated information.