AI Video Search and Indexing for the Media You Already Have

Most video libraries can only be searched by file name. The interview quote, the drone shot, the moment a product shows up on camera: it is all in there, but finding it means scrubbing through hours of timeline. ioMoVo takes a different route. ioHub connects the storage you already run, ioMoVo indexes every file in place, and ioPilot lets anyone on your team ask for what they need in plain language.

Every spoken word is transcribed and timestamped, so searching for a phrase takes you straight to the moment it was said. Text sentiment analysis then reads the tone of transcripts and documents, which helps with interview selects, audience feedback and media monitoring.

Vision and multimodal AI analyzes each uploaded or connected file down to the frame and tags the objects, settings and topics in every shot. Tags land on the asset as structured metadata that filters, workflows and portals can use right away, and your team can edit or remove them at any time. Inappropriate or offensive content is detected and flagged for review before an asset is shared or published.

Face recognition stays off until an admin turns it on, and it only identifies people you have registered as trained faces. Admins manage face metadata fields and people groups, and each group carries its own AI governance setting, so recognition follows the rules your organization sets.

ioHub connects AWS S3, Azure, Google Cloud, Ceph and other S3 compatible and on premise storage, and indexes your media where it sits. It needs read and write access to each store, so metadata, proxies and other derived files are saved right alongside your originals instead of in someone else’s cloud. For regulated and government teams, indexing and inference can run on premise or air gapped, so footage and metadata never leave your infrastructure. For hosted AI, bring the LLM provider you already trust, such as Azure OpenAI.