Data and human knowledge in a

Knowledge Graph for sustainable innovation.

Data and human knowledge in a Knowledge Graph for sustainable innovation.

Listening drives better decision making

By capitalizing on corporate knowledge, HIKUTM Innovation stimulates idea generation and encourages differing opinions to guide innovation. It creates a virtuous social dynamic that boosts corporate collaboration.

The team shares their knowledge on a specific domain by means of statements. Afterwards, these statements are combined and give rise to the decision-making scenario.

The data related to the functions and processes of the company are integrated with semantic logic, transforming into knowledge and generating value.


Machine Learning as a management consultant

HIKUTM makes it possible to capture and map the company’s objectives, defining variables and multi-level goals on the Knowledge Graph.

In this phase, the ML identifies the contradictions between the statements and stimulates the comparison between the team members, and carries out an activity of facilitation and functionalization of the processes similar to those of a management consultancy.


A product that transforms enterprise collaboration

The result is a composite virtual product, inclusive of viewpoints and objectives, that effectively accommodates ESG variables as well.

The complete navigation of this digital twin enables a new mode of interaction and collaboration, modeling the company’s operations to simulate its new product creation processes.


Analysis of risks and opportunities

The intelligence tool analyzes, through a back-end operation, an elaborated version of the graph where the business objectives to be reached are processed, identifying thanks to the knowledge the variables that influence them.

The analytics functionality supports and guides management in making the best decisions by integrating different areas such as design, sales, manufacturing and logistics.



Simulate scenarios and make decisions with a configurable AI

In addition to the software functionalities, HIKUTM makes the company’s Knowledge Graph operable in a simulation environment in which the company can choose the optimal solution for each problem over time.

In this phase, the data scientists proceed with the transformation of the graph into an inferable and predictive Neural Network to simulate and obtain sets of possible solutions that respect the constraints and maximize the required goals.