Intelligent Automation is a combination of Robotic Process Automation (RPA) and Artificial Intelligence technologies that together empower a rapid automation of end-to-end business processes and accelerate digital transformation.


Intelligent Automation combines RPA task execution with machine learning and process analysis, as well as cognitive technologies such as Computer Vision, natural language processing, and diffuse logic.
In addition, it covers the entire automation journey (discovery, automation, optimization), automating any front-or back-office business process and organizing work in teams made up of robots that mimic humans behavior.


Natural Language Processing (NLP)

Learning algorithms that analyze unstructured information.

Chatbots and virtual agents

Systems that can interpret voices or texts freely to provide predefined standard responses.

Decision systems

Systems that use deep learning technologies and cognitive abilities to recognize patterns. They also make possible the application of statistical models and algorithms.

Robotic Process Automation (RPA)

Automation of standard activities using scripts and other methods to support efficient business processes.

Natural Language Generation (NLG)

Technology that helps generate text while speaking or writing, from structured information such as fields and numerals.

Structured Data Interaction (SDI)

Traditional systems in which integration is made through the exchange of well-structured information.

Machine Learning (ML)

Systems that learn through iterations in advance, assimilating data learning and decisions.


Agility and precision
Fast and easy transaction processing with significant error reduction.

High flexibility
Ease of enabling and disabling capabilities within technologies compared to workforce. Ideal for operations with highs and lows seasons and variability.

Ease of deployment
They can be developed alongside existing IT structures with relatively low IT capacity requirements.

High availability
Robots are always available.




The client, derived from the situation presented with the pandemic, decides to analyze the creation of an ecommerce platform. After reviewing the implementation times and costs with different providers, it identifies that the prices offered by the Amazon logistics platform are unattractive and therefore decides to use third-party logistics.


Nubiral proposes an AWS-based solution that allows automating these processes through the S3 and lambda microservices. The solution automates the price query process for the different defined routes. In addition, once this information is consolidated through a CSV, the process of loading the SKUs with the different logistics values is automated.


The customer is now able to update their inventory in the Amazon Seller portal once a day without human intervention. This process previously forced the customer to only update the products and prices once a week, causing losses due to the increase in logistics costs (approximately 25%).



Capturing orders from the ecommerce platform and entering those orders in the ERP is a very manual process with a high percentage of errors.


The solution allows to automate the order capture process first, centralizing them in a repository, thus guaranteeing the consolidation of all daily orders in a single place.
Once they are consolidated, they must be entered into the ERP. This solution is 100% scalable.


The client will be able to carry out this daily process in 15 minutes without errors, when before it took between 4-5 hours. Even reaching processes to be carried out in real time.


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