Case Study: IntelligenceBank automates image tagging at scale and speeds asset discovery with Imagga

Automating Digital Asset Management process with image recognition

IntelligenceBank, a cloud-based Digital Asset Management (DAM) provider, faced a major challenge: customers uploading large image batches (often 50–300 images and in some onboarding cases up to 1 million photos a month) with little or no metadata, making manual keywording slow, inconsistent and impractical at scale. To solve this, IntelligenceBank evaluated vendors and selected Imagga’s Auto-Tagging API for its high object-recognition accuracy, rich keyword library and ease of integration.

Using Imagga’s Auto-Tagging API, IntelligenceBank automated keywording so images are tagged instantly rather than taking weeks or months of manual work, giving users a massive head start and removing a key barrier to DAM adoption. The AI-driven solution improved discoverability across collections (handling over 2.5 million images processed monthly), delivered better quality and landmark recognition for travel customers, and reduced tedious data-entry time while still allowing lightweight human curation.

IntelligenceBank

Tessa Court

Chief Executive Officer