Abstract
The Trust Engine Prototype proposes a modular, AI-enabled system for assessing the integrity of digital media content at scale. Designed to support democratic resilience, the system ingests large volumes of information across media platforms and evaluates them for factual consistency, semantic novelty, source behavior, and narrative coordination. By applying transparent scoring methods, it enables researchers, journalists, and civic institutions to detect coordinated disinformation campaigns, redundant propaganda, and manipulated media flows. The framework integrates signal normalization, provenance tracking, and claim verification tools to assign a composite integrity score to media entities and narratives. This public-interest infrastructure can operate in real time or retrospectively and is intended to support oversight, intervention, and public literacy. The white paper presents the system architecture, use cases, and feasibility arguments, contributing a scalable, accountable methodology to the field of information governance and political communication.
