Figueiredo Group Reduces Financial Losses by 15% with Python Automations

Figueiredo Group is a company with over 60 years of experience in the Brazilian market, specializing in the transportation of steel coils from steel mills.

14

robots in production

15%

reduction in financial losses due to operational errors

U$ 12,000+

in savings from operational efficiency improvements

Headquarters
Minas Gerais, Brazil
Industry
Logistics
Founded
1960
Company Size
201-500

Founded in 1960, the Figueiredo Group is a pioneer in specialized transportation of flat steel coils and wire coils. Continuously seeking innovative solutions, the company serves major steel mills in Brazil and is recognized as one of the most respected carriers in the market, known for its safety, quality, and punctuality.

With over half a century of experience in road freight transportation, the company boasts trained and qualified drivers and vehicles specifically designed to efficiently handle each type of product. The custom-designed vehicles are optimized to improve the loading and unloading process, reduce damage during transit, and minimize the risk of accidents on the road.

The organization’s strong suit is its commitment to security, from the loading of goods to their delivery to clients. The fleet is equipped with modern tracking equipment and is monitored 24/7, allowing clients to access real-time information on all stages of transportation.

Serving clients with efficiency, promptness, and reliability, the company operates across the Northeast, Southeast, and South regions of Brazil, achieving a prominent position in its industry.

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Automated Processes

Toll value reconciliation for 223 trucks

Issuance and monitoring of operational documents

Automation of web systems, shipper portals, and banks

Integration via API and Telegram for efficient communication

Challenge

The company faced significant challenges with controlling and monitoring these processes, including operational errors and incorrect toll charges due to outdated license plate information, leading to substantial financial losses. Additionally, errors in validating and reconciling transportation documents resulted in inefficient and slow processes.

“We were experiencing errors that led to significant financial losses — funds that could have been invested in new trucks, additional staff, or salary increases, for example.”

Helbert Carvalho, IT Manager

Figueiredo also aimed to automate the administrative tasks performed by its truck drivers. In addition to spending hours on the road, drivers could benefit from RPA robots to automate interactions via messaging, document sending, and validation.

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Solution: Python RPA for Loss Prevention

To advance the group’s automation project, the IT team decided to implement an RPA initiative using Python for its cost-effectiveness and flexibility in development and maintenance. The group successfully automated and optimized critical processes, such as automated toll value reconciliation and document validation via an app.

The orchestration of code-based automations with the BotCity Orchestrator and integration across various systems — including SAP, TOTVS Protheus ERP, web portals, banking systems, and communication platforms — enabled a more agile and efficient workflow. With Python, the automations became faster, and the technical support exceeded the team’s expectations.

Increased precision in execution and reduced errors allowed Figueiredo Group to save time and resources, redirecting efforts towards more strategic areas of the business.

“With automation orchestration, if an error occurs, an email is automatically sent to all managers notifying them of the issue, including the reason and whether it is a genuine error. TThis gives us the time needed to respond effectively.”

Helbert Carvalho

The advantage of Python is that automations are significantly faster, and BotCity’s support is far superior to that of other tools. I’ve had numerous issues with license renewals and support with low-code tools. BotCity’s license consumption is much more efficient for scaling.

Helbert Carvalho

IT Manager

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