"Simplifying complexity"
Cutting-edge advanced analytics for solving real problems
Evolution of analytics
Analytics has evolved from classical statistics to
self-learning algorithms, from:
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Modeling non-linearities with a high capacity.
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Incorporating multiple data sources.
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Delivering adaptive predictions in real time.
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Delivering greater precision and strategic context, among others.
That is, moving from retrospective analysis (descriptive and diagnostic) to prospective analysis (predictive and prescriptive); from information to optimization.
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Our focus
Predictive and prescriptive analysis for optimization based on the development of autonomous and semi-autonomous AI and Machine Learning solutions.
We transform data and content into deep knowledge to drive decision-making and execute automated actions.
Advanced mathematical modeling
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Development of complex mathematical models that are presented in processes.
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Simulation of scenarios for strategic and operational decision-making.
Operations research and optimization
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Application of optimization algorithms to maximize efficiency, reduce costs and improve the use of assets throughout the value chain.
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Optimization of production planning, operational continuity, predictive maintenance, inventory management and logistics routes.
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Optimization of resource allocation and scheduling of operations.
Complex Problem Solving
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Analytical and structured approach to address non-trivial technical and operational challenges.
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Interpretation of real-world problems in mathematical formulations to develop and deliver innovative and efficient solutions.
Graph theory
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Transport networks and supply chain optimization.
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Analysis of flows and bottlenecks.
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Modeling and optimization of supply chain.
