Technologies

Artificial Intelligence Tools

We are increasingly utilizing AI libraries to bring new functionalities and greater competitiveness to our projects. We have a comprehensive set of Artificial Intelligence tools that allow us to develop advanced solutions in various areas, some of which we use most frequently:

• PyTorch: Used in both image and text processing projects, providing flexibility and efficiency in developing Deep Learning models.
• Scikit-learn: Fundamental for traditional Machine Learning algorithms and data preprocessing, supporting tasks such as classification, regression, and clustering.
• Large Language Models (LLMs): Implementation of advanced models for natural language processing, enhancing our capabilities in tasks like text generation and semantic analysis.
• Optimization and Constraint Programming Libraries: Specialized tools for solving complex optimization problems and meeting specific constraints in our projects.
• OpenCV: For image and video processing, object recognition, and real-time vision applications.
• Detectron2 and Segment Anything: Advanced frameworks from Facebook AI Research for object detection and image segmentation.
• YOLO (You Only Look Once) and Similar: For real-time object detection with high precision and speed.
• MLOps: Integration of DevOps practices into the Machine Learning lifecycle to improve collaboration, reproducibility, and continuous deployment of models.

Development Frameworks

We focus on advanced frameworks that facilitate rapid and efficient development:

• Django: For the development of robust and secure web applications.
• FastAPI: For creating fast and scalable APIs, leveraging the advantages of modern Python and asynchronous programming.

Frontend Technologies

• React is our primary technology, allowing us to build dynamic and responsive user interfaces.

Technological Infrastructure

We have adopted modern and scalable infrastructures to support our applications and services:

• Kubernetes: For container orchestration, facilitating the deployment, scaling, and management of our applications across multiple environments.
• DevOps Methodologies: Implementation of DevOps practices that include Continuous Integration/Continuous Deployment (CI/CD), using tools like GitHub Actions.
• Containerization: Use of Docker to create consistent development environments and facilitate application deployment.