Data Exploratory Analysis

Customers data exploratory analysis

Data audit of the customer’s internal and external information sources, to gauge its data state-of-the-art regarding an AI project.

Data Science

Customers data exploratory analysis

Data loading, exploration, processing -curation and munging/wrangling, and data FAQ and no-FAQ.

AI Model Development

Customers data exploratory analysis

Applying a plethora of algorithms -or being the case, developing them from scratch, generating the proper AI model which can meet the customer’s requirements.


Financial Fraud Detection

Detecting fraudulent instances -customers, actions, events, etc.- through machine learning-based models with the highest precision.

Process Optimization

Improving business processes and procedures upon making use of machine learning techniques.

KYC & Churn Rate

Profiling customers through AI techniques to understand their business behaviors.

Real Estate Valuation

Developing an artificial neural network-based valuation platform from historic real estate valuations.

Power Trading

Trading power through a machine learning-based platform, optimizing supply, demand, and the spread.

Domestic & International Security

Browsing through structured and unstructured information sources by means of ontologies, natural language processing, and machine learning techniques to forecast, detect, and identify likely risks affecting the security of a country or an organization.

Who We Are

hAItta (入った), past tense of the Japanese verb hairu (入る), to enter.

When in January 2016 we decided to set up our company the message we looked to transmit was clear: The AI is already here. It has already ENTERED our lives and nothing is going to be the same anymore. This thought took us to choose the verb hairu (入る) in its past tense.

The AI is the result of the human excellence on researching, testing, improving in several fields of the human knowledge: Mathematics, Linguistics, Statistics, Computing, Commonsense Reasoning, Medicine... Following this rationale and to produce the company logo, we chose initially the Japanese kanji of hito (人), human being. To this ideogram we added two more strokes: one in the middle -crossing the original kanji, and one of the top. The resulting image became our logo in which human being and AI were blended; i.e., from the kanji of hito (人) the AI sprouted. Since the AI is a human being’s creation, hence the company mission:

Artificial intelligence serving human development.

hAItta is a Swiss artificial intelligence firm with international presence in Argentina, Colombia, Spain, and Germany.

Its working and research scopes are machine learning and natural language processing. Its solutions help decision making in different industries such as the financial, security, and transportation sectors.

An heterogeneous group of AI engineers, linguists, information analysts, computational engineers, mathematicians, and economists accompany the founding members: Mariano Ferrero, M.Sc. in Artificial Intelligence; and Domingo Senise de Gracia: M.Sc in Artificial Intelligence, MBA, and M.A. in Linguistics.

Strategic Partnership




Some of Our Success Stories

Organization: IATA
Organization size: 1,600 employees
Country/region: Worldwide
Industry: Aviation
Business need: Fraud and default detection on the flight ticket sale activity


Organization: Socierdad de Tasación
Organization size: 200 employees & 700 independent appraisers
Country/region: Spain
Industry: Real Estate
Business need: Improving Business Processes & Operations through Artificial Intelligence


Artificial intelligence Papers

Collective Decision-making through Multiple Criteria Determination and Preference Aggregation and Disaggregation Methods

Group Decision Support Systems (GDSS) can be essential in situations in which multiple persons are involved, each having their own private perceptions of the context and the decision problem to be tackled. Multiple criteria decision aid (MCDA) methods may be a useful tool in coping with such interpersonal conflicts, being required occasionally the preference aggregation and disaggregation methods to achieve consensus amongst the group members.

by Domingo Senise de Gracia

Engineered Bacteria and Nanotechnology – Different Approaches for the Common Goal of Removing Tumor Cells

In this paper two different approaches regarding the removal of tumor cells are explained. The first one is taken from the scientific article Environmentally Controlled Invasion of Cancer Cells by Engineered Bacteria; and the second one stems from the article A Smart and Versatile Theranostic Nanomedicine Platform Based on Nanoporphyrin.

by Domingo Senise de Gracia

Fuzzy Logic and Neurofuzzy System Technology for Stock Exchange Trading Strategy

This paper aims to present two distinct approaches to stock exchange trading based on fuzzy logic and neurofuzzy system technologies. The first approach introduces an intelligent decision-making model, based on the application of Fuzzy Logic and Neurofuzzy System (NFs) technology. And the second approach employs pattern classification methods using Artificial Neural Networks (ANNs), Fuzzy Inference Systems as well as Adaptive Neurofuzzy Inference Systems.

by Domingo Senise de Gracia

Nanorobots Destroying Tumors – New Perspectives on Cancer Treatment

In this article a simulation is exposed and explained in which a group of multi-agent nanorobots, after having been injected into a human body, search for a tumor in it and, as soon as they discover it, they gather and destroy it.

by Domingo Senise de Gracia

Ontology Information Retrieval through Natural Language Interfaces

In this article it is discussed the need to have a more user-centric attitude regarding the ontology retrieval information if our aim is to universalize this kind of knowledge representation, and to this end two approaches are introduced which follow this line of research: FREyA, an English natural language interface developed in the Department of Computer Science of the University of Sheffield; and a German natural language interface developed in the University of Applied Sciences RheinMain in Germany.

by Domingo Senise de Gracia

The Winograd Schema Challenge – A Step beyond the Turing Test

In this paper the Winograd Schema (WS) Challenge is explained: an alternative to the Turing test -the Imitation Game.The Winograd Schema Challenge is a test of machine intelligence proposed by Hector Levesque, a computer scientist at the University of Toronto, in 2011. It is a multiple-choice test that involves responding to typed English sentences of a very specific structure: they are instances of what are called Winograd Schemas.

by Domingo Senise de Gracia

Natural Language Processing for Human-Robot Interaction

It would simply reinforce what is evident, if it were stated: "Robots are becoming an essential part in our daily lives". Currently the use of robots in several and different industries is widespread. Nonetheless, how do we communicate and interact with robots? If robots are playing gradually a more important role in our day-to-day routines, we will have to develop humanlike dialogue-processing mechanisms to ease that interaction.

by Domingo Senise de Gracia

Classifiers Ensemble Selection

When a ensemble of classifiers is generated it has been shown that pruning it into a small number has better results. This article presents a review of some of the existing classifiers selection methods, both static and dynamic.

by Mariano Ferrero

Métodos y algoritmos determinísticos de inferencia aproximada en Redes Bayesianas

Existen dos grandes formas de tratar con inferencia en una Red Bayesiana: exacta o aproximada. En este artículo se pretende realizar una revisión de técnicas y algoritmos de este último tipo propuestas hasta la actualidad, particularmente aquellas consideradas determinísticas, las cuáles buscan reducir de alguna forma los cálculos requeridos para llevar a cabo esa tarea introduciendo simplificaciones en el modelo original

by Mariano Ferrero


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