In DEJAN's methodology, parametric memory represents the internal knowledge frozen into an LLM's weights during pre-training, operating independently from live web search. The platform interrogates this unprompted recall across different AI models using tools like the Treewalker engine, which evaluates token logprobs and alternative branching paths to extract raw brand associations. These ungrounded outputs are then curated into canonical claims and run through the Fact & Gap Checker, contrasting training-data memory against live research to expose model hallucinations, outdated beliefs, and missing brand facts.