Skip to Content

Context

An organization specialized in the financial and socio-economic analysis of Belgian companies based on the National Bank of Belgium annual accounts model.

Problem

The volume and complexity of data from annual accounts make analyses difficult.

Solution

Our AI software connected to a data warehouse that learns the hierarchical structure of the annual accounts model.

How is that possible ⬇

Our solution embeds a graph-based technology that allows the AI to structure its knowledge and establish complex relationships between pieces of information, enabling it to surpass competing solutions in terms of reliability and accuracy.

Context

A recruitment company receives hundreds of CVs every day.

Problem

The manual analysis of these applications — reading, data entry, and qualification — takes a considerable amount of time and greatly limits the operational efficiency of teams.

Solution

Our AI software connected to a structured database, fed in real time by an automation system that processes CV files as soon as they are received.









Video currently being edited.

How is that possible ⬇

Our automated AI system instantly processes incoming resume files, including images, to extract all relevant information and organize it into structured tables.

Context

An organic retail chain generating millions of sales data rows.

Problem

The client uses an ERP system, but the analytical capabilities of its BI module are limited, forcing teams to manually export data in order to perform their performance analyses.

Solution

Our AI software, connected to the company’s database, learns the client’s specific business requirements and operational logic.









Video currently being edited.