Investing in AI to make business decisions based on real-time, dynamic deep data insight.

Data Science

Henkel was struggling to manually process high volumes of customer invoices. Many were rejected, resulting in a complex and time-consuming invoice rejection handling process with no quantifiability. This meant that Henkel had tens of millions of Euros tied up in working capital, blocking ongoing business investment and incurring unnecessary financing costs.


Our solution provided NLP expertise to extract data in a structured format to enable analysis of previously unstructured and unanalysable data. 

We designed a sophisticated ocular character recognition and data extraction tool and built an augmented email view and dashboard insights to visualise data for management.


With our help, Henkel successfully achieved a number of improvements across its operations. Firstly, they significantly reduced the time required to identify and resolve errors, which allowed them to free up resources and costs. This enabled them to concentrate on providing more strategic support to their customers. Secondly, Henkel benefited from dynamic data insights, which greatly improved their decision-making processes and facilitated more effective resource allocation. Lastly, our collaboration with Henkel enhanced the company’s readiness for AI investments, unlocking valuable resources that can be utilized for future process enhancements, ultimately benefiting both their customers and internal teams.