Our solutions

The New Frontier of Corporate Productivity

The contemporary business landscape, reshaped by the challenges of the last decade, operates under a new premise: efficiency is no longer just a goal, but an imperative for survival and competitiveness. Organizations of all sizes and sectors face unprecedented pressure to optimize operations, increase supply chain resilience, and sustainably reduce operating costs. In this context, digital transformation has become the backbone of corporate strategy, and intelligent automation has emerged as its main value lever.

The Process of Building an Automation Solution

Implementing an RPA project consistently in your business is our specialty. Below is how we structure this process.

The Tangible Value of Automation: Proven ROI and Efficiency Gains

The justification for any technology investment in a corporate environment lies in its ability to generate measurable value. In the case of RPA, results are not only measurable but often fast and impactful. Calculating Return on Investment (ROI) is the core metric for evaluating the feasibility of an automation project. The formula is straightforward:

To apply this formula effectively, it is crucial to identify all costs and benefits associated with the project. Costs usually include purchasing software licenses, implementation and consulting fees, staff training and ongoing platform maintenance. The gains, in turn, can be divided into two categories:

All employees involved in operating the automated processes must be trained to use the new systems, ensuring that automation is both effective and safe.

1. Tangible gains: these are direct, easily quantifiable financial benefits. They include reduced human hours on automated tasks, increased productivity (more transactions processed in the same period), lower rework costs due to fewer errors, and the elimination of fines and penalties arising from compliance failures.

2. Intangible gains: although harder to quantify financially, they are just as important for the business. They include improved customer satisfaction and retention thanks to faster and more accurate processes, higher employee morale and engagement as staff are freed from monotonous tasks to focus on strategic and creative work, and stronger governance and auditability of processes.

The efficiency metrics achieved with RPA implementation are striking. Case studies and market analyses consistently show significant gains on several fronts. Companies report more than a 70% reduction in processing time for specific tasks and up to an 80% increase in overall process execution efficiency. The ability to operate 24/7 without interruption and to reduce human errors in automated activities to near zero are other frequently cited benefits.

Results of high-quality automation

When properly deployed and used, automation can generate consistent results and improve several aspects of your company, such as cost reduction, increased efficiency, better quality, greater security and more capacity to analyze and support growth.

The table below brings these and other examples together, turning theoretical benefits into proven business results and serving as irrefutable evidence of the value of automation.

These figures show that RPA‑based automation is not a long‑term investment with uncertain returns. On the contrary, it is an initiative capable of generating tangible value in a short period of time, which justifies its rapid expansion and prioritization on corporate strategic agendas.

RPA in practice: success stories from large Brazilian companies

In Brazil, major players across different industries are already reaping the benefits of mature implementations, consolidating automation not as a pilot project but as a strategic organizational capability. Analyzing success stories in key sectors of the Brazilian economy shows how technology is being applied to solve specific challenges and generate competitive advantages.

In‑depth sector analysis

The adoption of RPA and broader automation strategies is not a trend restricted to international markets. In Brazil, large companies in several sectors are already reaping the benefits of mature implementations, consolidating automation not as a pilot initiative, but as a strategic organizational capability. Looking at success stories in key sectors of the Brazilian economy shows how technology is being used to solve specific challenges and generate competitive advantages.

Energy sector

• Petrobras: The country’s largest energy company uses automation at an impressive and diversified scale. Petrobras invests in physical robots such as ANYmal X to perform autonomous inspections in hazardous areas, increasing safety and maintenance team efficiency. In its drilling operations, the company expects to save up to US$100 million per year by 2030 with rig automation, which also helps reduce CO₂ emissions. Beyond field operations, Petrobras applies hyperautomation in its corporate processes, partnering with companies like Wipro and ServiceNow to accelerate decision‑making and align IT infrastructure with the business. A case published by Automation Anywhere, citing savings of US$120 million in three weeks through automation and generative AI, illustrates the massive financial impact of these initiatives.

• Vibra Energia: The former BR Distribuidora established a strategic partnership to develop and deploy RPA in more than 40 areas of the company, resulting in an estimated saving of 380,000 work hours per year. In procurement, for example, automation reduced the average process cycle time from 41 to 28 days, optimizing supplier relationships. The company also uses automation to control refueling processes and manage inventory automatically, ensuring greater efficiency and reliability in product delivery.

Financial sector

• Bradesco: The bank is behind one of the most emblematic AI use cases in Brazil with BIA (Bradesco Artificial Intelligence). What began as an internal tool to help employees answer questions about products and services evolved into a robust virtual assistant that interacts with millions of customers via the app and WhatsApp, answering thousands of questions daily and performing transactions such as inquiries, payments and transfers. The maturity of the initiative led to the creation of BIA Tech, a platform developed in partnership with Microsoft that acts as a "copilot" for more than 2,000 of the bank’s developers, reducing coding time by up to 40%. At Bradesco Seguros, RPA is widely used to automate back‑office processes, claims analysis and pension plan portability.

• Itaú Unibanco: Brazil’s largest private bank treats automation and AI as pillars of its digital transformation, investing heavily in research and development through partnerships with universities and its own Itaú Institute of Science and Technology (ICT). Although specific ROI details are confidential, the scale of investment is a strong indicator of its strategic value. One survey showed the bank increased spending on AI by 120% in the first months of 2023, underscoring its commitment to the technology. Initiatives range from modernizing legacy systems and migrating to more agile platforms to building a technology ecosystem that underpins innovation in products and services.

• SulAmérica: The insurer is often cited as a leader in adopting automation and hyperautomation practices, integrating them with agile methodologies such as DevOps and Lean to optimize operations. A clear focus for the company is automating claims processes, seeking greater speed and accuracy in claims assessment and payment.

Retail and industry

• Magazine Luiza: The retail giant has technology as its main growth engine, centered at Luizalabs. This innovation hub, with more than 2,500 professionals, leads initiatives ranging from fully automating the logistics chain to integrating physical and digital processes. One of its best‑known projects reduced in‑store purchase time from 40 minutes to just 5 minutes. Currently, the focus is on developing generative AI to enhance "Lu", the brand’s virtual influencer, turning her into an intelligent shopping assistant capable of making complex, personalized recommendations.

• Ambev: The world’s largest brewery is building the "brewery of the future" based on Industry 4.0 concepts. The company uses a combination of automation, sensors and the Internet of Things (IoT) to monitor the entire production line in real time. This approach has led to a 15% reduction in energy consumption and a significant reduction in waste. Ambev’s automation strategy is so central that it created dedicated innovation arms, such as Ambev Tech and Z‑Tech, to digitize the entire ecosystem, from relationships with producers in the field to the end‑consumer experience.

The analysis of these cases reveals a clear pattern: the Brazilian companies most advanced in their automation journey have moved beyond isolated departmental projects. They have established dedicated organizational structures such as Centers of Excellence (CoEs) or innovation hubs (Luizalabs, Ambev Tech, BIA Tech, ICT Itaú) to govern and scale initiatives. These structures go far beyond simply implementing bots; they define the automation strategy, standardize tools, manage the project lifecycle and spread knowledge across the organization. For any mid‑sized or large company seeking to scale its automation efforts, creating a CoE is not optional, but a prerequisite for sustainable success.

Beyond the basics: the limitations of RPA and the need to evolve

Although RPA is a powerful entry point into automation, with quick returns and relatively simple implementation, a strategy based exclusively on traditional RPA often hits a "wall" of complexity. Many organizations, after reaping early benefits by automating simpler tasks, discover that the real challenge is scaling automation to more complex, higher‑value business processes. This difficulty does not stem from a flaw in the technology itself, but from its inherent limitations when confronted with the dynamic, unpredictable nature of the real corporate world.

The main technical limitations of traditional RPA are:

• Dependence on structured data: In its pure form, RPA is essentially "blind". It operates based on rules and depends on data presented in a consistent, structured way. It does not natively read, interpret or extract information from unstructured data sources such as email text, the content of a PDF contract, or fields in a scanned invoice whose layout varies from one supplier to another. This severely limits its scope, given that most corporate data lives in these formats.

• Fragility to change and exceptions: RPA bots are programmed to follow a rigid script, like actors who can recite only one set of lines. If any element in the environment changes — the position of a button on a web page, an interface adjustment in a system or a new step in the process — the bot "breaks" and stops working, requiring constant human intervention and maintenance. Likewise, business processes with many exceptions or alternate paths are hard to automate, because each variation would demand a specific rule, making the bot overly complex and hard to maintain.

• Automation of isolated task "islands": RPA is extremely effective at automating individual, discrete tasks. However, end‑to‑end business processes — such as procure‑to‑pay or order‑to‑cash — are complex value chains that involve multiple systems, departments and decision points. Trying to automate such complex flows using only RPA often results in disconnected "automation islands", where specific tasks are faster but the overall workflow remains fragmented and inefficient.

The main barrier for RPA, therefore, is not the technology itself, but the reality of business processes, which are inherently complex, variable and full of unstructured data. Traditional RPA works very well in a controlled environment with fixed rules and clean data. In the real world, however, things are "messy": invoices arrive in dozens of formats, customers communicate in unpredictable ways, and processes are full of exceptions that require human judgment. Traditional RPA fails in these scenarios because it lacks the cognitive ability to interpret context, adapt to variation or make decisions.

This leads to a crucial strategic conclusion: an automation strategy that relies solely on RPA is destined to hit a value plateau quickly. Companies automate the "easy", lower‑value tasks and then get stuck, unable to move on to automating the more complex processes that could generate the greatest transformational impact. This realization creates an urgent need to evolve toward a more sophisticated and holistic approach.

Welcome to hyperautomation: the strategy for end‑to‑end automation

The answer to RPA’s limitations and to the challenge of scaling automation across the entire company is hyperautomation. It is essential to understand that hyperautomation is not just a more advanced version of RPA or a new technology. Market analysts such as Gartner define it as a "business discipline" and a "strategic approach" that organizations use to identify, analyze and automate as many business and IT processes as possible. The ultimate goal is to move beyond automating isolated tasks and achieve true end‑to‑end process automation.

Hyperautomation achieves this ambitious goal by orchestrating an ecosystem of advanced technologies that work together. In this ecosystem, RPA remains an essential component, acting as the "digital workforce" that executes tasks. However, it is empowered by other tools that bring in the cognitive capabilities traditional RPA lacks. RPA is one piece of the puzzle; hyperautomation is the complete picture.

This shift from a tactical tool (RPA) to a transformation strategy (hyperautomation) is a crucial step in an organization’s maturity journey. It justifies investing not only in bots, but in an integrated automation platform capable of supporting more complex and dynamic processes. The table below highlights the key differences between the two approaches, illustrating this paradigm shift.