Solutions > Data > Applied AI
We develop AI & ML models that transform data into automatic and measurable decisions. We implement machine learning and applied artificial intelligence solutions with a real impact on processes, efficiency, and business results.
Why are AI and Machine Learning models important?
Predictive models and machine learning allow for anticipating behaviors, automating complex decisions, and optimizing operations, transforming applied artificial intelligence into real and scalable impact for the business.
Solutions within AI & ML Models
We combine different modeling capabilities to solve concrete problems and generate direct impact on operations and results.
Predictive models
We anticipate future behaviors such as churn, fraud, demand, or operational failures through predictive models trained with historical and current data.
Classification models
We implement automatic classification models and intelligent scoring to segment, prioritize, and make decisions based on probability and risk.
Optimization models
We develop models that identify the best possible decision considering multiple variables, constraints, and objectives, reducing costs and improving operational efficiency.
Recommendation models
We create recommendation systems that personalize experiences, optimize content, products, or internal processes based on behavior patterns.
Real stories, extraordinary results
Certifications and Partners
Our team has certifications in:
We use artificial intelligence tools that allow us to train, validate, and deploy models securely and at scale
ML Frameworks
TensorFlow, PyTorch, Scikit-learn.
Cloud AI platforms
AWS SageMaker, Azure ML, Google Vertex AI.
Training and validation tools
MLflow, Weights & Biases.
Our work process
We apply a structured process that ensures models transition from experimentation to production with real impact.
Understanding of the problem and the business
We analyze the context, the objectives, and the decisions that the model needs to improve or automate.
Data Preparation and Exploration
We evaluate the quality, availability, and relevance of the data to train reliable models.
Model design and training
We select algorithms and train machine learning models aligned with the problem.
Validation and performance testing
We measure accuracy, stability, and biases to ensure consistent results.
Integration into existing systems
We bring the model to production by integrating it with current platforms and processes.
Monitoring and continuous improvement
We monitor performance and retrain models to sustain results over time.
Specialized work team
Our service is supported by expert roles in applied artificial intelligence and machine learning, with a focus on productive models.
Data Scientist
Designs and trains predictive and classification models aligned with the business.
ML Engineer
Implement models in production ensuring performance, scalability, and stability.
MLOps Engineer
Automates deployments, versioning, and monitoring of models in production environments.
AI Architect
Define the AI architecture by integrating models with existing systems and platforms.
Staffing of artificial intelligence specialists
Through our staffing of artificial intelligence specialists, we incorporate professionals in ML, MLOps, and Data Science who integrate into your team to accelerate projects and maximize results.