Automatic Tagging: Picture identification by AI directly in CELUM
The success of a DAM project depends on the quality of the data. Assets without tags prevent an efficient search and therefore a comfortable usage. However, manual tagging or indexing costs a lot of time, money, and resources. With the AI Autotagging, this is history for CELUM projects.
AI Autotagging identifies and tags individual assets or whole folder structures per mouse click. This allows employees to focus on more important activities, free up resources, and take an essential step toward a successful DAM project. The AI Autotagging is an extension and therefore quickly integrated. The solution can be operated both as SaaS or on-premise variant.
6 QUESTIONS ABOUT YOUR DAM PROJECT
How many image assets do you have?
How many image assets are you adding monthly?
How many employees will be adding the assets in DAM?
Over what period?
How do you treat new assets?
What could employees do instead?
If you have the answers to these questions, you will clearly see the arguments for the automatic tagging.
In addition, the CELUM Autotagger pays back even more, the greater the amount or growth rate of the assets is.
MACHINE LEARNING: AI GETS TO KNOW YOUR PRODUCTS
Many companies have specific images, for example of their own products. The out of the box AI Autotagging may distinguish a swan from a sailing ship or a car from a house, but not distinguish a cappuccino from a latte macchiato. With specific training routines, the algorithms can get to know your products and include them in the autotagging. All that is needed are enough training images and of course visual differences between the products.