Smart video search is here

From TikTok to YouTube, video content is king on today’s internet. For years, video has made up a growing proportion of online content. Back in 2024, Personify predicted that videos would account for 82% of all consumer internet traffic in 2025, while streaming video would account for 91% of global internet traffic. In spite of these volumes, however, video search has historically presented challenges.

Video’s dominance makes it clear that creating a need for more powerful search tools, and as with many of today’s challenges, AI is there to offer solutions. Eidosmedia looks at how AI technology is dramatically extending the indexing and retrieval functions for both producers and consumers of video content.

Video search: yesterday and today

Throughout most of the web’s history, search has relied on crawlers that examine keywords and other text cues to understand what it’s reading and rank it accordingly. Simple, static images could use alt tags to make them quickly understandable to bots trying to make sense of visuals. Video, however, was an entirely different animal, which consisted of many images, audio, and sometimes text. Typical search processes were not designed for and, subsequently, did not work well for video.

The limitations of this kind of search and discovery were especially evident when trying to search your own video archives rather than, say, YouTube, where creators had good reason to tag their videos and make them as searchable as possible. Reolink sums it up: “Video used to hide insight. Reviewers had to scrub timelines or rely on sparse manual tags.”

Searching inside the video

Today, AI makes light work of the challenges of video search, making it infinitely easier. It goes beyond finding a video you might be interested in and instead “lets users find moments, people, objects, actions, or spoken words inside a video, the way you search a web page,” according to Reolink. Jasify defines three pillars that allow AI to make quick work of video search:

• “Computer Vision: Enables machines to “see” and understand visual content within video frames through object detection, scene segmentation, and action recognition
• Machine Learning Video Analysis: Provides the algorithms and frameworks that learn patterns from video data to make predictions and identifications
• Deep Learning: Powers advanced neural network architectures specifically designed for video understanding, including convolutional and recurrent neural networks”

Long gone are the days of asking an employee to sit, watch, and tag hours of video. AI systems can do it in minutes, allowing users to find insight that may have otherwise been buried deep in the middle of a video. Want to find an important statistic or quote shared in the middle of a webinar without having to rewatch, or fast-forward through, the entire presentation? AI can help.

Computer vision and object detection is at the heart of what makes this all possible. Simply put, it allows machines to process and interpret visual information. Scene segmentation chops up video content into segments, providing contextual understanding. This is what ultimately enables queries to surface specific scenes within long videos. Throw in facial recognition capabilities, and action and motion recognition, and you have systems that can recognize individuals and activities.

Practical applications of smart video search

The real question at the heart of the decision to embrace — or not — any new technological advancement is “Why?” When it comes to video search, the answer depends on your use case.

For content creators, using AI-enabled smart search can help with asset retrieval or even ensure style consistency across projects. Some engines go as far as to identify sentiment, themes, and genre. Forget something? Use generative fill tools to create elements that may be missing from your edit.

In an enterprise environment, the goals may be more mundane but no less useful. From simple discovery to creating transcripts — whether for accessibility purposes or just to make better use of existing content — to analysis, these tools can help employees save time and be more effective. These same tools can be used for content moderation; Vidizmo.ai advises, “Public-facing video content must align with brand values and avoid inappropriate or harmful material. However, manually reviewing each video before publication is time-consuming and often inconsistent.” AI tools can search and review public-facing video before it ever hits the web, potentially taking the onus off a human reviewer and speeding up publication.

Locating and monitoring consumer video content

In a media context, video search helps in a variety of other ways. From helping customers find new recommendations on platforms like Netflix to letting sports fans search for key moments in the big game, AI-driven search can help enhance user experience exponentially. And, it can help companies crack down on copyright infringement. Search tools allow media companies to identify unauthorized use of copyrighted material in user-generated videos. In fact, YouTube’s Content ID system is already scanning and flagging videos as they are uploaded.

In a post on LinkedIn, Redix Analytics Solution says retailers in the e-commerce space should also think about how video search can help enhance user experience: “A fashion retailer enables shoppers to upload a picture of an outfit, and the system finds similar items in their catalog using video search technology.” Meanwhile, almost any company can use video search to let employees look for specific content buried in training videos. Lawyers and law enforcement officials, on the other hand, can use video search tools to find specific testimony in depositions or to “locate a person of interest across multiple surveillance feeds, reducing manual review time.”

Integration is key

As video content grows in importance, having the right tools for its management is increasingly critical, even for organizations outside the strictly media sector. Among the caveats offered by Vidizmo, perhaps the most important concerns the integration with the organizational workflow:

" Select AI solutions that work seamlessly with your existing systems, reducing disruptions and ensuring smooth workflows."

As with other AI tools, close integration of smart video search facilities is key to reaping the potential awards in terms of productivity gains and added value.

About Eidosmedia

Eidosmedia is a global supplier of advanced content-management and digital publishing systems.

Its products are used by large news-media groups for print and digital publishing.

Customers include business dailies The Financial Times and The Wall Street Journal , as well as generalist news publications like The Times of London, The Washington Post and Le Figaro .

Find out more about Eidosmedia digital publishing solutions.