Powerplay has launched an AI Workforce platform for the construction sector, introducing five domain-trained AI agents to automate workflows across estimation, procurement, finance and project management. The platform is designed to improve operational efficiency, with early deployments showing a reduction in estimation timelines from weeks to minutes and productivity gains of 50–60 per cent across key processes. Built on data from over 85,000 construction projects executed using Powerplay’s software, the system leverages insights from bills of quantities, procurement cycles, billing workflows and compliance records to standardise execution processes. The AI agents cover functions including estimation, procurement, supplier qualification, demand forecasting, compliance and working capital readiness, operating within real-world construction environments. Commenting on the launch, Iesh Dixit, Founder and CEO of Powerplay, said, “Construction is one of the largest industries in the country, contributing nearly 9% of GDP and employing millions of people, yet it continues to operate with a persistent shortage of specialized expertise - from estimation engineers to procurement coordinators. What we’re seeing globally is the rise of vertical AI - systems trained on real workflows that can automate work in industries that were previously too complex for generic software. Construction, with its fragmented processes and heavy reliance on manual coordination, is one of the most consequential frontiers for that shift. For us, AI was a natural evolution - the models finally caught up to the data we had built over years. Our ambition is to make sure India is not just adopting this transformation, but helping lead it.” The platform incorporates a human-in-the-loop model, ensuring AI outputs are reviewed before decision-making, with accuracy levels of up to 99 per cent. Powerplay plans to expand AI capabilities across the entire project lifecycle, targeting adoption among contractors, infrastructure developers and project firms seeking improved cost, timeline and execution predictability.