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Search Smarter, Not Harder: How Visual Search AI and eyebase uncover Hidden Value in Your Media Library

This solution goes far beyond simple image comparison it understands the content of a scene, analyzes visual structures, and creates meaningful connections across your image and video collections. All without the need for prior tagging or manual metadata.

How Visual Search Works

Visual Search AI from Datamachine leverages cutting-edge artificial intelligence to identify visually similar images across your entire archive instantly, accurately, and without the need for manual preparation or labeled training data. Unlike traditional search methods that depend on text-based metadata or keyword tagging, this technology understands the content of an image on a visual level. By analyzing the overall composition, objects, textures, colors, and context within the image, the system can detect similarities even when files are poorly tagged, completely untagged, or have been altered – whether through cropping, mirroring, editing, or compression. It recognizes not just the presence of individual elements, but the relationships between them, enabling truly semantic visual discovery. This scene-based understanding eliminates the limitations of conventional search and opens up new possibilities: finding images you didn’t know existed, linking different versions of the same content, or uncovering connections between media that previously went unnoticed. It’s a smarter, more intuitive way to explore your visual assets.

Value Delivered

Visual Search adds a new layer of intelligence to your image and video archives by creating structure where there was none before. Instead of relying on manual tagging or inconsistent metadata, the system visually analyzes and connects assets based on their content. This results in faster access to relevant files, even when they are poorly labeled or not labeled at all. By accelerating large-scale migration projects, reducing time spent on daily search tasks, and enabling more accurate categorization, Visual Search transforms how teams across departments interact with media. It empowers users to surface hidden relationships between assets, enrich content discovery, and unlock insights that would otherwise remain buried. Whether you're managing digital collections in a museum, streamlining media workflows in a newsroom, or optimizing product imagery in e-commerce, the added value is measurable and immediate.


Privacy by Design

At eyebase, we believe that innovation should never come at the cost of control. The Visual Search AI was developed with a strict privacy-by-design approach. Every analysis is performed without storing or transferring your images externally. Your media files never leave your environment, and ownership of your content remains solely with you. No images are used to train the model, no content is repurposed for product development, and no visual data can be reconstructed or reverse-engineered from the system’s index. This ensures full compliance with data protection standards and gives you the confidence to use powerful AI technology without compromising the integrity or confidentiality of your digital assets.

Use Cases – More Than Just Search

1. Accelerating Image Ingest

  •  Duplicate Detection: Automatically identify identical or nearly identical images, regardless of resolution or file type.
  • Linking Versions: Recognize high- and low-res versions, negatives, or digital copies of the same content.

2. Supporting Daily Workflows

  •  Collection Check: When adding new items, compare them visually against existing content.
  • Faster Annotation: Reveal hidden knowledge in your archive to support faster and more accurate tagging.
  • Search Without Keywords: Upload an image to find similar items, no need to enter any text.
  • Series Recognition: Identify images that belong to a visual set.
  • Partial Image Search: Crop a section of an image to find matching content.
  • Detect Misplacements: Find files that are incorrectly stored or categorized.
  • Outdated Content: Locate assets with expired rights or relevance.
  • Watermark Detection: Check if stock images have already been licensed or if alternatives exist.
  • Spare Parts Search: Help field service teams locate items based on an image alone.
  • Insurance Claims: Detect reused or altered images submitted in previous claims.
  • Video Search: Extract visual highlights to create a searchable timeline of your video content.

3. For Public Engagement

  •  Visual Browsing: Let visitors navigate collections through image similarity, without needing to understand metadata.
  • Smart Suggestions: Offer visually related content based on what the user is viewing.

  •  Fewer Returns: Help webshop customers find exactly what they need reducing return rates.

Conclusion: The collaboration between eyebase and Datamachine opens up a new era in visual data discovery. Whether you're managing an archive, curating digital assets, or running a media-driven platform – AI-powered Visual Search is more than a tool. It's a game-changing companion that adds structure, speed, and intelligence to your visual workflows.

Ready to experience it? Discover a new way of searching with eyebase and Datamachine and book a demo to see Visual Search in action.