Improving efficiency in the reverse

engineering of flavouring

The challenge

A multinational company in the chemical industry sector is dedicated to the generation of aromas (perfumes and fragrances). To do so, it starts from raw materials and components and combines them to obtain the desired aroma.

Objectives

To automate the process of obtaining aromas using reverse engineering.
Improve the efficiency of the process.
Achieve combinations that more accurately reflect the desired flavour.
Standardise, structure and centralise data and process knowledge within the corporate

Services performed

Artificial Intelligence
Machine Learning
Gradient Boosting Machines
Optimisation
MLOps

Vue.js
Django
Python
SQL
ETL

Results provided

The solution has helped speed up users’ time in creating flavour formulas.