Visual Intelligence for News Archives and Broadcast Monitoring

News broadcasters generate and store an enormous volume of visual content every day. Over the years, this builds into a massive but largely untapped archive - footage from press conferences, protests, political debates, on-the-ground reporting, and more. Often, these archives are minimally tagged, making it difficult to extract insights or repurpose material quickly.

Tiliter’s Vision AI Agents allow newsrooms to turn that unlabelled video into structured, analysable data.

Using advanced computer vision, our solution can:

• Detect and label individuals, such as politicians, public figures, or repeat interviewees
• Recognise objects like protest signs, brand logos, police vehicles, and other context-specific details
• Track crowd size, behaviour, or movements across time and geography
• Identify recurring visual patterns or trends across different news cycles or regions
• Extract timestamps and contextual tags to enrich metadata and support content licensing

This enables editorial and research teams to:

• Search archives visually, not just by captions or titles
• Quantify screen time for topics or figures (e.g. election coverage fairness)
• Spot patterns in event coverage, helping assess bias or repetition
• Build new content faster by finding reusable footage based on visual relevance
• Enhance compliance reporting by proving diversity, balance, or content mix
• Create monetisable datasets for external use (e.g. media monitoring firms, researchers)

For real-time broadcasts, Vision AI Agents can also flag key visuals as they appear - helping producers highlight breaking developments, detect misinformation cues (e.g. altered footage or reused imagery), or streamline fact-checking.

By turning passive footage into an active source of structured intelligence, Tiliter helps news organisations better manage, use, and monetise their visual assets.