Our platform is able to capture numeric and textual data from various sources and formats. These sources (websites, documents etc.) can be both external and internal data provided by our clients. There is no need for our clients to provide the data in a specific format, we transform it in a way that is processable for us.

A huge number of texts from diverse documents and sources need to be analysed and categorised through a Natural Language Processing stack.

One of the core features of our AI technology are semantic taxonomies for information structuring.

The objective of this process is the generation of analysis and predictive information in the form of ratings, scores, etc. Such results are based on input variables stemming from various data sources.

The platform elaborates KPIs and thresholds based on the previous NPL analysis.

Our prediction engine makes DYDON unique. Dydon AI’s proven Predictive Reasoning methodology combines several soft computing methods (i.e. mathematical formula, point scoring, rule-based aggregation, fuzzy-logic and NeuroFuzzy) to intelligently link and aggregate uploaded or via text analysis extracted input values.

This concept provides full transparency for both the aggregation process and the generated results. Both are important elements to achieve explainable AI results.

Results are presented in an understandable way. For example, our decision trees allow to drill down to specific results. Our graphics are fully customizable to fit to your needs.