DEJAN captures and parses raw grounding metadata across major AI platforms—such as Google Search grounding chunks, OpenAI response annotations, and Anthropic search tool citations—to differentiate between selected citations actually referenced in generated text and unselected sources merely retrieved during web browsing. By resolving redirect URIs to canonical domains and tracking trust ratios, the system isolates why certain retrieved pages fail to convert into active citations.

To improve citation conversion, this telemetry feeds directly into a Bayesian snippet optimization loop and veracity scoring engine. These tools systematically test extractive page variants and monitor whether brand claims survived, were lost, or became distorted during model synthesis, ensuring authoritative placement and accurate representation in AI-generated answers.