At WeHandle, one analyst closes the monthly payroll in two hours, with CLT employees and contractors in the same place.

WeHandle has hundreds of people, and almost half of them are contractors. The company manages third parties for large companies: when one of them hires outsourced labor, WeHandle checks that the supplier is in order, from its documents to its payroll.

It uses AI to read those documents instead of a person, and the next step is already being built: predicting a supplier's risk before opening its first document.

Checking the documents of thousands of suppliers gives Rodrigo Faustini a view of the labor market that almost nobody has.

He often cites that 60% of the world's formal workforce is outsourced, and that 70% to 80% of those suppliers leave their payroll with an accounting firm.

The mistakes he finds in those payrolls are in the details, like unpaid weekly rest (DSR) and a wrong match with the union agreement. An accounting firm serves many clients with the same process, and each one's details slip through. A mistake like that starts small in one month's payroll and comes back as a liability the following year.

WeHandle's CLT payroll sat with an outside accounting firm. Contractors were tracked by hand in a spreadsheet, and almost half of the company's workforce are contractors, so that spreadsheet carried real weight. To know who was active and who reported to whom, someone had to match the two sides by hand. Caio Sagae, the CFO, wanted one place to see both.

Tamiris Dias took over HR in that setup, with no record of who was active or who led whom, and with onboarding, vacations, terminations and the payroll close requested from the accounting firm by email and spreadsheet.

This arrangement is what the market offers by default, and it worked. WeHandle decided it wanted more than it delivers.

Caio's criterion was to see CLT employees and contractors together, in the same place, and Tako was the first option he found that handled both that way, with the contractor next to the employee.

Tamiris brought two questions to the conversations with Tako: what set it apart, and why switch from the partner she already had. What reassured her was understanding what Tako did differently from the systems she already knew: taking manual work off the team and putting the data in the hands of the people who run the operation.

Anyone thinking about moving payroll away from an accounting firm usually has two fears: losing people's history and getting the first close wrong. WeHandle made the switch at the turn of the year. Tamiris ended the relationship with the accounting firm, extracted the full people and payroll history and brought all of it into Tako, where the first payroll of the year already closed.

Tako's implementation team worked alongside her on the first payrolls, checking the history and recalculating whatever was needed until the close matched, which was what worried her most. Caio describes the handover as smooth because it was followed closely.

With the history inside Tako, Tamiris no longer depends on third parties for any information, and a new HR initiative starts with the data ready.

Larissa Baldin closes WeHandle's payroll on her own, and most of the manual work is out of her way. The time clock now feeds payroll directly, so nobody types in hours worked. Whatever repeats every month is set up as a recurring entry and comes back on its own in the next pay period. Onboarding became a link the new hire fills in, which took document and bank detail entry off the payroll team.

What is left for her is checking and deciding, and that fits in two hours.

Larissa, Caio and Tamiris ask questions about the operation in the AI tool WeHandle already uses, connected to Tako's data through the MCP. Each of them found a different use, and none of them goes through a report.

Tamiris moved into a more advisory role, close to Rodrigo and the leadership team, on fronts like hiring and performance reviews, work the operational load used to leave no time for.

Caio sees a change broader than the finance team. For him, the line between HR, finance and legal shrinks once AI comes in, and everything moves toward a single back office organized around people data, the company's main asset.

Larissa follows a company that grows without the payroll team having to grow at the same pace, which gives her time for the work that takes judgment.

Tamiris wants HR to see a problem before it shows up, and for recognition and performance to be decided with reliable data, at the pace WeHandle grows.

Rodrigo thinks about a lower layer. For him, AI will become infrastructure, the way electricity and water already are, and then nobody needs to think about it. Work that repeats every month, like running payroll or reviewing one more document, stops being done by people once that infrastructure exists.