Teaching machines to learn

Technology to serve people

We are a multidisciplinary team of people specialized in software development, artificial intelligence, infrastructure design and management and data analysis, and we build innovative solutions.

By leveraging the potential of data and AI, we give technology the ability to see, listen and speak, turning it into an ally for your future strategy.

All fields of artificial intelligence within your reach to help you make the best decisions for your business

  • Computer Vision

  • Conversational Assistants

  • Natural Language Processing

  • Edge Computing

  • Advanced Analytics

  • Data Visualization

  • Data Architecture

  • Process Automation

  • AI Garage

«We cover the artificial intelligence domain comprehensively, from data processing to the application of the latest advances. We are able to automate processes just as people do naturally».

José Luis Calvo Head of Artificial Intelligence at SNGULAR

We automate everyday processes through simple and accessible solutions.

  • Alfred

    Alfred is a conversational assistant model trained to answer more than 70 questions related to the administration and human resources departments of companies and to perform tasks automatically (broadcasting messages, creating reminders, requesting vacation days, booking meeting rooms...).


    Alfred can be deployed on Slack, Google Chat and Microsoft Teams and it is fully customizable.


    Alfred se integra con Slack, Google Chat y Microsoft Teams. Además, es totalmente personalizable.

  • Corex

    Corex is our system for creating and designing conversational assistants that enables us to fully customize their conversation style and content and connect them with third-party services. In addition, this platform allows us to develop highly scalable chatbot projects for all types of companies.


    Chatbots are a powerful internal communication tool that fosters company culture, thus reinforcing corporate identity.

  • Taleet

    Taleet is a SaaS that maps an organization's talent by generating relationships between employees based on their skills. We start from different data sources and an algorithm that creates a first version of the profiles (CVs, LinkedIn, GitHub...).


    Through its skills extraction engine, Taleet manages to detect relevant information among thousands of resumes from your company and creates an interactive map you can navigate through. In addition, Taleet learns continuously and is able to segment talent and detect similar profiles within your organization.

  • Morph

    Based on our experience in both Big Data and Small Data, we have created Morph, a flexible platform that allows us to provide fast, scalable and easy to maintain solutions to facilitate business decision making.


    Morph collects data from various sources and processes it in a centralized and scalable system to provide analytics or visualization solutions and create useful dashboards or reports.

The creation of Naturgy's chatbot

The virtual assistant team had the opportunity to work with Naturgy's innovation area to create its chatbot, called Pepe. This assistant helps customers learn more about the company's energy plans, promotions and actions, answering more than 500 questions in a practical and swift way. In its first 15 months, Pepe handled more than 90,000 user queries, resolving 92.5% of sessions on its own.

Aprende más sobre el proyecto de Naturgy

Santander Universities: dropout rate prediction

Using a dataset that collects the academic performance of university students, we performed an exploratory data analysis to choose those variables that best predicted a student's potential academic dropout.


Using Machine Learning algorithms such as Random Forest or Support Vector Classifier, we conducted 288 experiments.

More info

Event detection to predict the occupancy of the Barcelona transport service. PoC for TMB

Proof of concept for the creation of a system for automatic detection of events that may cause delays in the usual route of a passenger, with the aim of suggesting better alternative routes.


Some examples of event detection are breakdowns in a subway line, cut off streets, weather incidents, traffic density, holiday schedule or changes in the route of a bus line.

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