Researchers propose a new approach to improving the reliability of text-to-query and tool-using AI agents by grounding them in knowledge graphs. This method, called symbolic separation, involves using a Virtual Knowledge Graph to validate and constrain agent actions, resulting in improved task success rates, reduced data-integrity errors, and cost savings.