Carlos Espinal

The turning point in the early days of UiPath was shifting our mindset - instead of building the next big feature that made sense to us as developers, we built what our customers needed. This same philosophy is what enables us to help customers surpass the exploratory and POC stages of enterprise level AI-adoption. Our approach to agentic automation is to enable our customers use the right tool for the right task, and allow people to have visibility into what agents produce - unifying AI agents, robots and human decision making into a single platform. Continental Resources is one of our customers and early adopters of agentic automation. Their solution is now in production, showcasing the right balance between AI-driven processing and human intervention. They chose a use case that tackles a common but high-stakes problem in the energy sector: accurate classification and routing of technical drilling data. This process would historically involve engineers manually reviewing and classifying emails, extracting well and stage data, verifying accuracy, and uploading files into internal repositories. By orchestrating agents, robots, and built-in decision flows to escalate inconsistent or incomplete data, they reduce manual oversight, increase data accuracy, and accelerate information availability for engineering teams. Early feedback indicates strong results, with the agents achieving high accuracy scores in identifying and classifying emails within an hour of deployment.