Deep explorer
Knowledge Graph
function description
Turning data lakes into added value
The Knowledge Graph plays a crucial role in connecting objects or people, creating the basis for faster and more precise searches. This not only enables better recommendations, but also makes knowledge transfer much easier. In a matter of seconds, it generates added value for both editors and viewers.
When researching two people and their connections, the Knowledge Graph is an invaluable sparring partner. Its ability to identify relevant information and commonalities at lightning speed makes the process much easier. The Knowledge Graph not only serves as a basis for research, but also plays a crucial role as a database for Large Language Models. This link makes it possible to provide verified information to counter hallucinations or falsehoods in GPT texts.
For editors who have spent years building up their knowledge, the transfer of this expertise is often a challenge. The Knowledge Graph provides a solution by giving this knowledge a structured form. This means that not only experienced editors can benefit from this wealth of knowledge, but also young colleagues who want to produce news directly.
benefits
Transforming data into value
Faster access to information and connections
Reliable
LLM
Encouragement of knowledge transfer within the newsroom environment
use cases
Knowledge Graph Use cases
CGI OpenMedia
OpenMedia, powered by DeepVA AI, optimizes journalism workflows—from research and story planning to scripting, multi-platform output, and rundown management.
how it works
How does Logo Recognition work?
Logo Recognition analyses logos for various characteristics and compares them with the database behind them. This database can be either pre-trained personalities or your own training material. In addition to face and landmark recognition, logo recognition will also be adapted to the specific needs of companies in the future.
