Success stories
Falabella
What if technology could predict failures before they even happen?
THE CHALLENGE
Manually creating detailed descriptions (colors, sizes, materials) for thousands of products.
The process was slow, error-prone, and caused launch delays.
THE SOLUTION
Using advanced AI, Mindtech:
- Applied Gemini Pro Vision to analyze images and extract visual attributes.
- Used Gecko to enrich descriptions with comparative text.
- Deployed on GCP, Python, and Docker for scalability and speed.
THE IMPACT
Over 10 product templates filled per day automatically.
Fewer errors in product information.
Faster e-commerce launches.
A smoother, more reliable customer experience.
Fewer errors in product information.
Faster e-commerce launches.
A smoother, more reliable customer experience.
In retail, speed and accuracy are everything.
As the leading department store chain in the region, we faced a major challenge: automating product descriptions to improve efficiency and customer experience.
Benefits
Improving product descriptions on the online store to enhance the customer shopping experience and increase sales.
Substantial reduce the time needed to input product attributes by leveraging cutting-edge technologies.
Challenge
The process of completing product attributes was cumbersome and time-consuming. It also resulted in incomplete or error-filled product descriptions, impacting the user’s shopping experience
Solutions
Using computer vision, we generated product descriptions which contain information about attributes such as color, material, dimensions, size, etc. This information is published on the ecommerce along with the product images. The project is based on the use of AI generative models, specifically Gemini Pro Vision, to achieve three main objectives:
- Create new product descriptions by extracting attributes from product images.
- Enrich these product descriptions using previous information from other products.
- Perform a retroactive process to update the product descriptions when new attributes are found when compared to embeddings generated by Gecko (Google model), i.e., add this information to existing similar products.
Benefits
Improving product descriptions on the online store to enhance the customer shopping experience and increase sales.
Substantial reduce the time needed to input
product attributes by leveraging cutting-edge
technologies.
Challenge
The process of completing product attributes was cumbersome and time-consuming. It also resulted in incomplete or error filled product descriptions, impacting the user’s shopping experience.
Solution
Using computer vision, we generated product descriptions which contain information about attributes such as color, material, dimensions, size, etc. This information is published on the ecommerce along with the product images.
The project is based on the use of AI generative models, specifically Gemini Pro Vision, to achieve three main objectives:
The project is based on the use of AI generative models, specifically Gemini Pro Vision, to achieve three main objectives:
- Create new product descriptions by extracting attributes from product images.
- Enrich these product descriptions using previous information from other products
- Perform a retroactive process to update the product descriptions when new attributes are found when compared to embeddings generated by Gecko (Google model), i.e., add this information to existing similar products.
Google Cloud Platform (GCP) was chosen for its robust cloud computing capabilities and built-in machine learning services, providing a reliable infrastructure that is highly scalable for heavy computational tasks.
Python was selected as a high-level, interpreted language with an abundance of AI-related libraries, allowing for easy readability, quick prototyping, and sophisticated AI and machine learning projects.
Docker was utilized to automate deployment and scaling of applications, ensuring the consistent operation of the AI model across various environments.
The Gemini Pro Vision Model and Text Embedding Gecko Model were used to offer specialized functionalities in computer vision and natural language processing respectively, providing capabilities such as sophisticated analysis of visual content and representing text data as normalized numerical vectors.