Retail sector
Retail
In a world where consumer expectations are constantly evolving, retail companies must adapt quickly to stay competitive. QUANT AI Lab offers solutions that allow companies to: analysis of consumer behavior, stock management, price optimization & omnichannel experiences.
Omnichannel Experiences
We help companies integrate physical and digital channels, offering a coherent and attractive shopping experience on all platforms.
Stock Management
We use machine learning algorithms to optimize inventory and the supply chain, minimizing waste and improving operational efficiency.
Price Optimization
We develop dynamic pricing systems based on market demand and competition, maximizing profits without sacrificing customer satisfaction.
Consumer Behavior Analysis
Through data analysis, we identify purchasing patterns and customer preferences to develop more effective and personalized marketing strategies.
View use cases
Data & AI Roadmap
For clients undergoing digital transformation and looking to integrate AI to optimize their operations and stay competitive, it’s essential to develop a realistic, results-oriented operational roadmap.
Exploring Internal Data
This project has the goal of providing a general and adaptable solution. In the following section, a specific use case is presented, which was developed as part of a hackathon.
Fraud Engine
With the large volume of transactions occurring daily in e-commerce, it is necessary to monitor and validate all of them to ensure their integrity.
Retrieval fashion system
The project involves developing a fashion retrieval system using deep learning.
Sales-Driven Unit Distribution
The model addresses the problem of distributing 𝑋 units across multiple categories to each store in such a way that the resulting stock ratios after the shipment closely resemble the sales ratios from the previous day.
Smart Tagging
One of the main issues our e-commerce client was facing was not knowing at detail all products they have.
