Part of the team at Fhinck, a Brasil-based AI startup capable of analyzing operational efficiency data from people, processes, and platforms, identifying employees close to burnout or even areas that could be automated, arrived this week in Tampa, Florida. Despite serving corporate customers in six other countries, including Brazil, and many more through partners, the company is opening an office in the United States intending to test its solutions in the most competitive market in the world and win over more global customers.
Today, Fhinck already serves companies such as Accenture, Unilever, Natura, and Kroton, among others. According to Paulo Castello, founder and CEO at Fhinck, who has previously worked for companies such as Walmart, Marfrig, Nokia, and Odebrecht, the startup‘s expansion plan, founded in 2014, has been in place for some time.
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“We have already mapped the five regions where we need to be. In addition to the United States and Brazil, Central America (Costa Rica), Eastern Europe (Poland), and Southeast Asia (Malaysia) are on the list. These are regions where large corporations go because there find cheaper workforce, tax incentives, and where more than one language is spoken,” says Castello, noting that it is also through these regions that companies test and hire services that will later serve the entire corporation.
Among the many uses Fhinck’s tools can have, Castello ‘found himself’ in the area of hyper-automation, one of the top 12 technology trends for 2022, according to Gartner. “There are so many applications, but when I read more about hyper-automation, I saw that this is exactly where Fhinck fits in.”
New features
Fhinck recently released two features in line with this idea. One of them is “Task Mining,” which maps tasks performed and transforms them into real-time indicators. This capture of indicators is done without depending on any integration with other systems. As a result, it can help the company identify bottlenecks, costs, the lack of quality, and even show the status of extensive periodic routines, such as accounting.
“The algorithm will identify, for example, how many Control C+Control V are made, adding this variable to others, such as how many systems the employee needs to use throughout the day, which will indicate the degree of complexity of a given journey and area. Thus, the system ranks the areas most likely to be automated. In summary, activities of lesser complexity and more repetition are usually at the top [of this classification]. This is done through a score: when it is low, it indicates automation; when it is very high, it indicates high complexity, and then the ‘remedy’ is not automation, but the standardization of tasks to reduce this complexity,” explains Castello.
According to him, while companies typically make top-down decisions for this kind of improvement and investment, Fhinck’s solutions generate bottom-up insights and, therefore, are more assertive.
In addition, Fhinck also recently launched a “Virtual Assistant” feature, a robot that talks to the user and, based on data and interaction with the machine, offers personalized recommendations and insights to increase professional performance and improve the digital experience. The assistant also cares about health and well-being, measuring screen time, suggesting breaks during the day, and pointing out the need to get up, stretch your legs, or hydrate yourself with a glass of water.
Organizations can also use the same functionality to trigger communications, measure employee satisfaction, conduct surveys and interact with employees remotely. “This technology allows for ‘less control’ and more autonomy for professionals, as they receive daily feedback from the flow of tasks, if these are repetitive, as well as points for improvement for a lighter, self-confident and more efficient journey,” highlights Castello.
Fhinck’s solutions can be purchased in a self-service model through an annual subscription. And although it starts standardized, the algorithm behind the applications, says Castello, learns and customizes itself for each company. All the insights generated can be followed through an integrated dashboard.
Castello did not disclose revenue or other company metrics because he is negotiating a Series A round, the first in the startup‘s history.
