The power to transform the way we make decisions in our work environment.

Thanks to the application of artificial intelligence, you can now significantly improve the productivity of an organization, increase customer satisfaction, optimize costs, among many other competitive advantages. However, many companies still do not know how to successfully adopt AI.

Leaving aside the concept of artificial intelligence exploited by science fiction, at Mototech we specialize in one of the best-known branches: Machine Learning and its more complex version Deep Learning.
These solutions focus on the massive collection of data within the context of a problem and the identification of patterns and relationships between them, to obtain knowledge creation as a result.

What stage is my company in?

If we transfer the concept of knowledge generation to a company, we will easily find multiple lines of work in which we can provide added value, however it is important to have the vision of an expert who can advise you regarding the stage of maturity in that your company is to deal with this type of solutions.


Having a large amount of data and with as much refinement as possible is the first phase of maturation of a company to address artificial intelligence solutions. Machine learning algorithms feed on data, and the accuracy of the knowledge generated will largely depend on the volume and cleanliness of the data.

Companies that are at this stage could be at an early stage solving the data capture and processing process, or they have already captured the information but have not yet found added value.

To correctly resolve the capture stage, it is essential to design an architecture and data management according to the objectives pursued. We suggest relying on AWS, GCP or Azure cloud tools to facilitate scalability as data grows, as well as reduce development times with the use of these services.

Finding value in data involves working with data scientists to create visual representations of data to find patterns, trends, and outliers to help better understand the reality of your business.


The correct definition of the objectives to be achieved, together with the metrics to quantify the degree of success of the solution, are essential for data scientists to be able to apply their knowledge in selecting the algorithm that best suits the problem and evaluate the same in development iterations.

Our team has the necessary experience and tools to select the appropriate algorithms for each particular problem. These algorithms are used to learn patterns in your data and develop the model or models from which we will obtain the expected knowledge.

Just to mention a few:

Algorithms for Natural Language Processing (NLP) when working with texts; for example for the classification of documents, the extraction of entities or the sentiment analysis of a post on social networks.

Algorithms for Image and Video Processing when we work with data in which we seek to detect objects and classify content.

Predictive Algorithms when we work with tabular data to perform advanced analytics in order to obtain recommendations.


Where do I start? What is the process? Can AI be applied to my business?

To guarantee successful results, at Mototech we suggest that the different problems of your company be addressed with a Proof of Concept scope in such a way that the potential of your data can be evaluated with the minimum possible investment and in the shortest possible time.

The process we recommend for getting started with an AI solution is as follows

Analyze the state of the art

Investigate solutions similar to what you want to solve, identify public data sets and pre-trained models that could define a baseline for the project.

Train a model that allows evaluating the prototype

Data scientists’ expertise is put to the test by modifying existing algorithms and adding new data to train improved models.

Analyze the metrics and data that were obtained as a result

Evaluate the performance of the inferences obtained with the previously trained model, analyze possible improvements and start new iterations.

Productize the prototype

For the vast majority of problems, in one or two months it will be possible to complete the proof of concept and have clear information to be able to decide, with a fraction of the cost of the project, the viability of the solution and what can be expected from it.

We would love to accompany you on your Artificial Intelligence project. Are you ready to take the next step?

We craft beautiful and unique digital experiences, providing robust hyper-automation solutions based on artificial intelligence to face the challenges of the 4.0 world and lead the true digital transformation of your company

If you have an idea, it’s time to turn it into a reality & find the estimated cost.



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