Intelligent technologyfor the digital world.

Utilizamos el potencial ilimitado de la IA para crear la tecnología del próximo siglo; con el objetivo de resolver las necesidades de los negocios digitales, aplicando una inteligencia de software pionera.

Ecosistema Big Data

Combinamos la potencia del Big Data con las capacidades de análisis y visualización que ofrecen las herramientas actuales.

Análisis Cognitivo

Agentes virtuales multiplataforma capaces de interpretar el lenguaje humano y responder entablando una conversación.

Machine Learning

Sistemas que identifican patrones complejos a partir de incalculables volúmenes de datos, siendo capaces de predecir escenarios de forma fiable.

01. Ecosistema Big Data

Big Data Architecture

Own Big Data architecture, orchestated with data-centered layers: data transformation, storage and processing, exploration and management, and data serving trough APIs.

Data Science

Implica metodologías, procesos y sistemas para extraer el conocimiento y la comprensión de los datos en sus diferentes formas, ya sean estructuradas o no estructuradas, y de múltiples fuentes.

Predictive Models

Advanced analysis that uses new and historical data to predict future activity, behavior and trends. Applying the Predictive Model Markup Language (PML), and using Application Programming Interfaces.

Data Analytics

Including data collection, integration and visualization services, enterprise analytics solutions, social media and digital outreach, policy analytics and decision support, and data quality assessment.

02. Análisis Cognitivo

Artificial Vision

Capture and analysis of visual information using a camera, with an efficiency and precision far superior to the human eye, including from identification of signatures to analysis of medical images.

Natural Language Processing

Understanding the real meaning  of any query that is executed (semantics). Through computational linguistics, computers can decipher human language, being able to imitate a conversation.

Cognitive Computing

Uses many of the same fundamentals as AI, such as ML, ANNs, NLP, and sentiment analysis, to follow the problem-solving processes that humans do. Systems that learn at scale, reason with purpose and interact with humans.

Artificial Neural Networks

Based on a collection of connected units or nodes called artificial neurons, ANNs are computing systems that learn progressively by considering examples, generally without task-specific programming.

03. Machine Learning

Unsupervised Learning

Dimensionally Reduction (Meaningful compression, structure discovery and Big Data visualization) and Clustering (Customer segmentation, targeted marketing and recommender systems).

Reinforcement Learning

Focused on real-time decisions, robot navigation,  artificial intelligence in gamification, Skill acquisition and learning tasks. Trial and error method to discover the best rewarded actions.

Supervised Learning

Based in building patterns, including classification (Customer retention, fraud detection, diagnostics) and Regression (Marketing and sales forecasting, estimating and growth predictions).