PicPay Internal AI Platform Reaches About 90% of Staff

On August 24, 2026, PicPay (PICS) disclosed on an earnings call that about 90% of employees were using its internal AI platform, with most using it daily, while the number of product deployments had doubled since the start of the year. The company did not disclose the deployment baseline, quality results or technology-expense savings.[1]

How the employee AI platform fits PicPay

PicPay (PICS) is a Brazilian digital bank that provides consumers and small and midsize businesses with a digital wallet, payments, cards, credit and other financial services. It earns revenue from transactions, interest and various financial-service fees. The Employee AI Product Development Platform helps internal staff use AI for coding, design, quality assurance and real product deployments. Because it participates directly in delivering financial products, it is part of core operations.

The application has only one citable public disclosure, dated August 24, 2026. It was already in limited production and used across the company when first observed. Management described platform use, employee participation and deployment changes together, but did not explain any earlier pilot or expansion steps. The evidence confirms that AI had entered active product development, but not how it evolved before that point.

What the adoption and deployment metrics show

About 90% measures how broadly employees use the internal platform, while most employees using it daily indicates that use is not occasional.[1] The same disclosure showed that 30% of employees had participated in real PicPay product deployments since the start of the year and that the number of deployments had doubled. These metrics connect adoption to workflow output, but do not show how many deployments each employee made, the size of each change or the absolute starting base.

More deployments could improve the output efficiency of technology spending. If AI enables more roles to participate in coding, design and quality assurance within engineering standards, PicPay could complete more product iterations with similar investment. Deployment count does not measure product value, however, and defects, rollbacks and rework could offset speed gains. The company also did not separately connect platform use to technology expense, staffing needs or revenue changes.

PicPay has shown that its internal AI platform achieved company-wide adoption alongside broader employee participation and higher deployment volume. The evidence confirms increased product-delivery activity, but not a lower cost per deployment or improved company profitability. The next critical evidence is deployment volume reported on a consistent basis, together with defect rates and technology expense per deployment.

Application assessment

• Employee AI Product Development Platform | Business position: Core operations | Deployment stage: Limited production | Scope: Company-wide | Value type: Cost reduction

Sources

[1] Drillr · PICS (PICS) · 2026-08-24 · Earnings call

Original: We also have agents and people using our internal platform for credit development. So, they are supporting coding, designing, credit assurance. Nowadays, approximately around 90% of our employees are actually using our AI platform, with most of them using it daily. We have, like, from the beginning of the year, we have 30% of employees that are contributing with deployments, real deployments for PicPay products. And most of them, such as myself, wouldn't be able to contribute without AI, right? We're not actually told that's possible, so there are more and more people contributing and with real products. And the number of deploys actually doubled from the beginning of the year because of that productivity.