In Retail & Fashion there is a significant gap between what customers buy and what is produced and stocked, leading to unsold inventory, off-price sells, order cancellations and resource waste.

This has huge Economical, Brand and Environmental impact.

Artificial Intelligence can improve merchandise planning, reducing this gap with predictive models built on SKU features, both known and hidden, gathered from sources such as ERP, technical sheets, pictures, natural language or ecommerce data.

With data-driven decisions aided by machine learning models, brands can make smarter choices in assortment definition and source the right product variants in the correct quantity for each market to reduce risks and maximize profitability.

Guarantee Margins

To guarantee margins it is important to focus resources on the articles with most potential. This also reduces risks and costs associated to failed product launches, minimizing waste and markdowns.

Leverage customer feedback

Leveraging information from customer behavior and sentiment is a must for designers and product portfolio managers.

Reduce Time to Market

Predictive feedback in design and sales campaign can help you achieve a dramatic reduction of time between the idea of a new product and its launch on the market.

About Us

Predit is a startup born in 2016 and based in Milan. Predit is part of Techedge Group, a leading IT services and solutions provider and partner of major technological platform vendors, in particular SAP and Google.

At Predit we ideate, develop and market cloud-native predictive applications for Fashion & Retail and actively work with Google to promote adoption of Cloud solutions and Machine Learning in the industry.

Predit help brands make smarter decisions in product development and merchandise planning, maximizing profitability and reducing risk and costs of unsuccessful products.



Davide Tresoldi


Riccardo Nava

Data Engineer