At Piazza Copernico we believe in the combination of knowledge and the possibility of understanding the operating logic of the models.
This is why we want to offer to owner of the data and to analyst specific functions and tools for working with the results of the analyses, so that they can be understood, questioned and above all brought back into the work processes.
SEMANTICASE UPDATES
From this perspective, the software semantic case is constantly updated, combining the procedure and robustness of semantic data analysis with the ability to generate data LLM.
With the integration ofGenerative AI the ability to understand textual data and the activity of exploration, questioning and interpretation of the results is further consolidated.
The current state semantic case stands out for specifically designed and controlled models, in particular with respect to:
- to the importation of multiple sources and to valorisation of the text as "data", with appropriate pre-processing tools,
- atno-bias analysis of the data, with a wide parameterization of available models to be adjusted based on the data,
- to the scalability models from small to large texts,
- atgenerative AI activation on specific phases of data analysis,
- to the data visualization, which today is integrated with generative AI.
A TOOL THAT IS ALWAYS UPDATED AND NOT "FALLUCINATED"
Today semantic case represents a rich and parameterizable tool, which enhances different algorithms NLP, integrating in a controlled way the LLM in the analysis and visualization steps, with an adequate parameter setting a keep bias and hallucinations under control.
semantic case allows you to use the most interesting ones Open source LLM (LLaMA, Mixtral, Solar) depending on the project characteristics, and our R&D team continues to constantly monitor and test the emergence of new models.
All analyzes take place on dedicated servers, without using APIs towards third party services, with certainty of cost and guarantee of confidentiality.
semantic case it remains a procedure that aims to be at the service of the data, with a user friendly process, adaptive to the analysis needs, but not automated.