Creating and training a deep-learning model to simplify existing formulas, resulting in 30% reduction in number of ingredients while keeping end formulas identical in 99% of cases
Customer
Creating and training a deep-learning model to simplify existing formulas, resulting in 30% reduction in number of ingredients while keeping end formulas identical in 99% of cases
Customer
Developing a state-of-the-art forecasting approach by combining multiple forecasting models to achieve a 97-98% accuracy, leading to monetary and time savings
Customer
Developing a state-of-the-art forecasting approach by combining multiple forecasting models to achieve a 97-98% accuracy, leading to monetary and time savings
Customer
Developing a Deep Learning model to optimise existing formulas resulting in
a better consumer test score for AI optimised formulas compared to the originals
Customer
Developing an algorithm to determine optimal formula composition alternatives to reduce costs by up to 50% while keeping a similar molecular quality
Customer
Establishing a search engine to aggregate and facilitate access to product data for R&D activities, resulting in faster search times and decreased research costs
Customer
Creating custom statistical algorithm to define optimal “logistic bases” for formulas in order to minimize the amount of pouring and reduce costs
Customer
Analysing a production line to improve production speed and anticipate slow-downs resulting in 15% speed-up with a 8x ROI
Customer
Creating automated web scraping tool to augment data assets with external web data in near real-time leading to best-in-class data analysis and AI models
Customer
Training a deep neural network to predict end product properties without having to actually mix ingredients together, reducing development cost and time
Customer
Creating an API platform to facilitate access to insights from various models from different systems, laying the foundation for more ML use across the company
Customer
Optimising combination of different ingredient batches to maximise molecular composition consistency of products overtime
Customer
Conducting a ML model assessment and delivering a comprehensive report confirming the direction taken by the internal team and foresting innovation
Customer
Defining an mathematically optimal manufacturing sequence order to reduce total production time of perfumes
Customer
Developing multi-modal tool to enable transformation of image or text description into an fully-fledged perfume
Customer
Customer
Customer
Customer
Implemented deep learning models able to predict the main characteristics and traits of finished products, along with potential market fit