How do you choose the best platform for your Artificial Intelligence project?

It is a known fact that Artificial Intelligence (AI) is the biggest factor when it comes to creating competitive advantages for businesses today. The vast majority of companies are looking for ways to apply AI to their business and processes, and unfortunately most have failed to achieve the expected results. One of the most important reasons is the lack of a structured data platform to create the data foundation needed to understand the business and apply AI.  There is a wide range of options available in the market for creating the Business Intelligence Platform, and choosing a disconnected AI strategy platform can lead to hidden costs and low performance of analysis, views and predictive models.

With that in mind, Augmented Intelligence and Bravo Logistics Services started a great partnership at the end of last year, and are on the verge of rolling out their project. Some company departments have already begun data structuring and management, which will soon spread to other areas of the company that specializes in logistics.

The whole process until the optimal project is reached depends on analyzing pre-existing information and an elaborate analysis of the products available that can meet the company’s needs. “The first step in choosing the most appropriate cloud and data platform is Data Governance Architecture Definition, which consists, among other steps, in collecting functional information, understanding Business rules and systemically mapping out information, all of which enables us to recommend a BI Platform that is the best fit,” explains André Scher, the CEO of

In the case of Bravo Logística, according to CEO Marcos Vilela Ribeiro, automation with data management was a natural need for the company. “We understand that with the changes the world is going through, we needed to evolve and use new technologies for our business. We started this data management project with our IT team supporting the needs of the business areas, but with the increase in demand we concluded that we needed to organize a centralized database and generate autonomy for the business areas to handle their information through business intelligence,” he said.

According to Bravo’s 4PL operations manager, Marcos Azevedo, the company was looking to update the data in the system in near real-time, instead of having to update it manually, several times a day. “With this automatic and near real-time update, we’ll be able to make faster decisions when there is any problem or an opportunity for improvement, which will ensure lower costs, more agile service and, ultimately, a more satisfactory return for our customers,” he concluded.

André Scher points out that several possibilities were taken into consideration for Bravo Logística in order to suggest the most appropriate platform. “We need to take into consideration aspects such as usability, resiliency, scalability, UX, data security and governance and cost, and it needs to be a future-proof,  lock-in free platform. We looked at options like AWS, Google, Microsoft, and within them BigQuery, Aurora, Databricks, and more.”

According to the CEO of auctus ai., the next steps consist in building the platform (creating the data bank, ETL, data input and data collection and scrubbing) and building the BIs (Front-End design, Dashboard development and UX definition for the new BI’s). “But it is useless for the company to have all this technology at its disposal, if employees are unable to get the best out of it. That is why key user and support are essential,” says Scher.

Another important point mentioned by André Scher is the cost of implementing such a project. “Nowadays, any company in any industry and of any size can and should benefit from the existing BI platforms to add value to its business. The initial investment is really small when compared with the benefits and it’s even possible to do everything using free platforms if the client so wishes and if it fits into the company project. You just need the right professional to run the studies and projects,” he says.

Once the data has been structured and the platforms are up and running, the company can going beyond traditional Business Intelligence and run predictive and prescriptive analysis, allowing it to predict behaviors (weather, labor strikes, fuel prices, toll hikes) and ensuring a more efficient product or service deliver, with greater time and cost efficiency. “Bravo Logística handles the shipping and storage of different agricultural products, and having information that facilitates and optimizes these processes provides extraordinary gains for their operations, as they can provide even more efficiency and value to its clients’ logistics chain, allowing services to be faster, improved and more profitable,” concludes André Scher.


About – Augmented Intelligence

Belonging to the Innovatech Group, offers consulting services and develops solutions based on data science, artificial intelligence and business process automation (RPA).

The business purpose of is to provide customized solutions capable of reducing costs and improving the experience of our clients’ customers through the application of data science and intelligent process automation, where we automate not only repetitive tasks, but also integration between systems, using unstructured data and generating insights and predictions for making business decisions.

The solutions of can be applied in small to large companies, in business processes that are common to all financial, administrative, customer service, human resources and IT companies, among others.