Metadata at depth
Structure rich title, people, theme, mood, language, franchise, and other available content attributes into a more expressive content layer.
trackbinge.
Explore a partnership
TrackBinge turns rich media metadata and contextual signals into custom viewer-behaviour models—so streaming platforms can move beyond “what was watched” to understand what a viewer may want next.
Model-led personalisation. Metadata-rich context. Recommendations built for your product.
Titles are more than genres and star ratings. We bring together deeper content attributes and contextual relationships to help power useful, explainable recommendation experiences.
Structure rich title, people, theme, mood, language, franchise, and other available content attributes into a more expressive content layer.
Model preference signals and viewing-context patterns to represent evolving interests—not just broad audience segments.
Use model outputs, vector search, and contextual retrieval to support discovery, ranking, and relevant next-watch suggestions.
TrackBinge is envisioned as a B2B intelligence layer that can complement existing streaming products, content catalogues, and discovery journeys—rather than asking partners to replace their stack.
Organise available media metadata into connected, searchable content representations.
Combine permitted interaction data and context to learn preference signals, with privacy and consent considered from the outset.
Expose recommendation candidates, similarity signals, or ranked results through an integration designed around partner needs.
Potential integration conversations can span metadata providers, title-discovery services, and entertainment knowledge bases.
We’re interested in exploring complementary B2B use cases: metadata enrichment, cross-catalogue discovery, recommendation services, and contextual audience intelligence.
Have a catalogue, recommendation challenge, or platform use case to explore?