With a primary search system that dated back to the 80s, and several siloed systems holding more than 11 million hours of video and audio files, the ABC (Australian Broadcasting Corporation) wanted to change the archive search experience for their content makers and internal users.
There were multiple warehouses across Australia filled with physical reels, several disconnected metadata systems, and five separate on-premise systems storing the content that had not yet been digitised. These legacy systems were costly to maintain and almost impossible to scale.
Previously, any content categorisation or archive retrieval was done manually. The process of finding content would take several weeks as it typically required a manual search of at least three databases. Kablamo envisaged a new cloud digital platform and search experience to unlock the value of the broadcaster’s archive media, and we would use machine learning to get there.