AI Autotagging and Classification for Searchable Content Libraries
Automatically tag videos using speech, captions, on screen text, and visual signals. Classify content into governed categories such as archival, restricted, or redaction required to support search, compliance, and review workflows.
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Tag Videos Automatically Based on Topic and Theme
Teams upload videos fast, then skip tagging because it takes time and the tags stay inconsistent. EnterpriseTube generates tags based on the video’s topic and theme so content stays organized from day one.
Generate Tags from Transcripts and Spoken Keywords
When titles and descriptions stay short, key terms live only inside the audio. AI transcription turns speech into searchable text, then you can use those terms as tags and metadata.
Extract on Screen Text with OCR for Stronger Tagging
Demos and screen shares contain part numbers, case IDs, and slide text users search later. OCR detects text on screen, handwritten notes, and license plates, then stores them as searchable metadata and tags.
Add Visual and People-Based Tags with Video AI
Some searches depend on what appears in the video or who is present, not only what is said. Object detection and facial detection let teams tag videos by visual elements and identified people to refine discovery.
Enrich Metadata with Advanced Visual Insights
Basic tags do not always capture tone, context, or brand presence inside video libraries. Optional insights such as emotion recognition, brand detection, and sentiment analysis add extra signals for smarter search.
Classify Content into Governed Categories Automatically
Manual classification leads to gaps in governance, retention, and access control workflows. Rule-based classification and contextual analysis apply labels like archival, non-archival, restricted, or redaction required at scale.
Can Be Used For
Organize meeting recordings at scale
Auto tag town halls, weekly syncs, and leadership updates so teams can find decisions and topics faster.
Improve in-video search for training libraries
Use transcription, OCR, and visual metadata to tag steps, terms, and on screen content inside long recordings.
Find people and objects in video footage
Use face detection and object tags to retrieve clips based on visual cues and identified individuals.
Support investigations and case review
Search inside evidence using spoken words, on screen text, and visual signals, then jump to relevant moments.
Classify content for governance and review
Automatically label files as archival, restricted, or redaction required to support compliance workflows.
Frequently Asked Questions
AI Autotagging extracts signals from video and documents to generate tags, metadata, and classification labels automatically.
Tags come from topic detection, speech transcription, OCR, visual analysis, and extracted keywords from captions.
Classification assigns labels like archival, non-archival, restricted, or redaction required using rules and contextual analysis.
Yes. Tags and metadata support in-video search so users can open content at the exact moment where a match occurs.
No. AI reduces effort, while users can still add or adjust tags and labels to meet business requirements.
Videos benefit most, and the same classification and OCR capabilities also apply to images and documents.