Longitudinal cardiology care requires integrating information scattered across multiple visits, yet key details remain embedded exclusively in free-text notes. We present an end-to- end pipeline that transforms heterogeneous visit-level documents into a longitudinal timeline by (i) extracting structured events from individual encounters using large language models and (ii) consolidating semantically equivalent entities across visits into unified clinical trajectories. The resulting representation captures diagnoses, symptoms, medications, including dose/regimen changes, and vital signs, enriched with clinically relevant quali- fiers such as negation and uncertainty. The structured timeline is exported as machine-readable JSON and presented through an interactive HTML dashboard with synchronized visual panels. This interface supports rapid temporal exploration, episode-focused review, and integrated inspection of conditions, therapies, and physiological signals.