A department store chain with extensive coverage across Mexico struggled with time-consuming product attribute completion, resulting in incomplete or error-filled product descriptions that negatively impacted the shopping experience. Mindtech implemented AI-powered computer vision technology using Google's Gemini Pro Vision model to automatically extract product attributes (color, material, dimensions, size) from product images. The system enriches descriptions using historical product data and uses Text Embedding Gecko to retroactively update similar products with newly discovered attributes.

Falabella's manual product description creation was time-consuming and error-prone, resulting in incomplete or inaccurate product information that negatively impacted the e-commerce customer experience and delayed platform launches. Mindtech deployed AI-powered automation using Gemini Pro Vision for computer vision analysis, Text Embedding Gecko model for semantic enrichment, and GCP infrastructure with Python and Docker for scalability. The system extracts product attributes (color, material, dimensions, size) from images, enriches descriptions using comparative data, and retroactively updates existing products with newly discovered attributes.

A prestigious private university in Latin America needed to modernize its AI-driven assistant solutions. While previous chatbot initiatives existed, evolving AI capabilities required upgrading services to optimize response times while maintaining accuracy and scalability. Mindtech developed two primary AI solutions: an Academic Bot allowing professors to upload course materials to tailor responses for their classes, and a Regulations Bot designed to help students and faculty navigate university policies. Built with FastAPI, Python, Azure, and OpenAI models using Agile and DevOps methodologies.

A major global automotive manufacturer removed hood temperature sensors from one vehicle model to reduce costs. Without sensor data, they couldn't proactively detect engine failures occurring in tropical markets where black-colored vehicles experienced overheating issues. Mindtech implemented an Early Fault Detection (EFD) system using machine learning clustering with Sentence Transformers to analyze customer claim comments, UMAP dimensionality reduction to identify fault patterns, and vehicle model variables and quality process data integrated into predictive models, deployed on GCP infrastructure.