Intervention

Integrate AI automated tagging with custom metadata models

This intervention is required when a specific in-house metadata model is in use - e.g. a taxonomy or a knowledge graph - in order to give valuable results in a custom domain.

Solves these Problems

Experts cut corners when applying metadata to assets

Expensive and slow to manually apply custom metadata at scale

Improves these Problems

SME resources wasted on low-value manual tasks

Involves these Technologies

Automated Content Tagging using Artificial Intelligence (AI)

The use of AI or Machine Learning (ML) to automatically predict content classifications. This is also known as "Auto-tagging" or "Auto-coding" (Healthcare applications) or "Auto-classification".

Artificial Intelligence (AI)

AI is a core discipline at Data Language, with an expert team skilled in machine learning, deep learning, and scalable Production AI engineering. AI is advancing as the key technology that all businesses need to master.

Graph databases

Mobilized with these SaaS features

Supports custom classes

Ability to support 100s or 1000s of classes, outside of the standard "People, Places, Organisations, Themes" pattern

Knowledge Graph DAM (Digital Asset Management)

Data Graphs provides Knowledge Graph DAM capabilities: interconnected media asset management and delviery - images, video, video moments, audio, and more - with highly structured, connected graph metadata.