DataScope, the Chilean startup specialized in software for operations management and field work, is promoting a new regional expansion process with a focus on Latin America. Founded in 2016 by Nicolás Serrano, Antonio Grass and Carlos Carvajal, the company digitizes processes such as inspections, maintenance, workplace safety and quality control through mobile forms, workflows and real-time data analysis.
Currently, the platform is used by more than 300,000 users and more than 600 companies in 17 countries. Based on this growth, DataScope is consolidating its operational presence in Chile, Peru, Brazil, Colombia and Mexico, with active teams and clients in each of those markets and a multilingual support strategy in Spanish, English and Portuguese that facilitates implementation in different contexts.
Datascope: Organic growth and a different bet
Unlike most startups in its segment, DataScope has built its regional expansion with a model close to bootstrapping. Since its founding, the company raised capital only through a round in 2022 through the Broota investment platform, betting on sustained and profitable growth rather than an aggressive escalation financed with debt.
Today the team is made up of 43 people distributed in different countries in the region. “We want DataScope to become the operational basis for work in Latin America, allowing more and more companies to manage their processes in the field with reliable and real-time data,” said Nicolás Serrano, founder and CEO of the company.
Artificial intelligence for field work
The key metric the team monitors for 2026 is the number of actions executed within the system, that is, tasks that were previously performed manually and are now automated. The company’s objective focuses on tripling the figure during the year and reaching 1.5 million automated actions monthly.
In parallel, DataScope began to incorporate artificial intelligence tools aimed at summarizing operational findings, detecting patterns, and anticipating deviations in processes. A commitment that seeks to take the platform one step further: from digitizing work in the field to anticipating problems before they occur.
