Visual AI
Transforming traditional asset management with Artificial Intelligence
Enhancing DAM
Businesses and organizations are constantly flooded with an overwhelming amount of digital assets. From images and videos to documents and presentations, managing these assets efficiently is crucial for streamlined operations and successful marketing campaigns.
DAM systems such as Filerobot provide a centralized hub for organizing, storing and distributing digital assets. And even though DAM solutions have revolutionized the way digital content is handled, their potential can be further amplified by combining them with Artificial Intelligence (AI). This leads to better asset management, enhanced user experiences and increased productivity.
The integration of AI with DAM is, without a doubt, a game-changer in the world of asset management. The various benefits it offers, including automated tagging, improved search, intelligent content recommendations and efficient content moderation, highlight its enormous potential.
With AI-powered DAM systems, organizations can optimize asset management, deliver better user experiences, and ultimately achieve increased productivity. As technology continues to advance, the relationship between DAM and AI will continue to evolve, empowering businesses to harness the full potential of their digital assets and stay ahead in the competitive digital landscape.
Scaleflex Visual AI
Visual AI is a set of machine-learning models hosted by Scaleflex to accomplish advanced image and video recognition and enrichment tasks. Built with powerful technologies, it powers up productivity and efficiency with AI & ML. By intelligently extracting information from any media assets, it helps clients stay ahead of the competition with faster content workflows.
Scaleflex Visual AI greatly improves Digital Asset Management with market-leading AI & ML automation that create dynamic ways to screen, retrieve and govern digital assets.
The following pages describe the various services that provide automation to solve multiple digital media challenges.
Note about integration
All request examples you will find in this documentation are synchronous calls to our API. They will help you to understand our response formats and help you to assess the quality of our models. However we strongly recommend that you integrate our API using the asynchronous mode. The reason is that our servers have throttle limitations to avoid being overflowed.
Asynchronous requests will not give you the response directly but will give you an URL that returns the status of the task and the final results when they are ready.
To use the asynchronous mode add the following query parameter to your request :
Here is an example of an asynchronous request :
Here is the response of the asynchronous request:
Here is the response of the status URL before the task is finished :
Here is the response of the status URL after the task is finished :
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