AI-assisted tagging for a company video library

The company had accumulated a substantial video library, but the material was effectively opaque: finding a specific moment, topic, or asset meant scrubbing through footage or relying on whoever remembered it.

Tagging the library by hand was the obvious fix and the one nobody would ever finish.

We use AI to do the volume work and structure to make it trustworthy: model-generated tags conform to a defined vocabulary rather than free-form text, so the output is queryable data, not more unstructured content.

The pipeline is designed for review — tags are attributable to their source and correctable, so the library gets better with use instead of drifting.

Biotite built an AI-assisted tagging pipeline that processes the video library and produces structured metadata: what the material contains, organized against a controlled vocabulary designed with the client.

The result is a searchable index over the library, maintained by the pipeline as new material arrives.

A video library that was searchable only through people's memory is now a structured, queryable asset.

New material enters the library tagged, so the index stays current without a standing manual effort.