Warehouses are generating more data than ever, but turning that data into faster decisions remains a challenge. Takt is now looking to close that gap after raising $9.25 million in new funding to expand its warehouse labor management and intelligence platform.
Takt Secures $9.25M Series A
Takt, a Reston, Virginia-based warehouse labor management and intelligence company, has raised $9.25 million in Series A funding. Ballast Point Partners led the round, which marks Takt’s first institutional financing. The company announced the funding on August 17, 2026.
Founded in 2021, Takt develops technology that brings labor, automation, and robotics data together. Its platform is designed to give warehouse operators a unified view of their operations and help them make decisions while work is still underway. Takt currently supports more than 100 warehouses across North America and international markets. Its customers include Fortune 500 retailers, global brands and some of North America’s largest third-party logistics providers.
Bringing Labor and Automation Data Together
Modern distribution centers often use several technologies at the same time. Labor performance, automation systems, robotics, time and attendance tools and warehouse management systems can each generate separate sets of information. Takt aims to bring these data sources together into a single operational model. Its platform helps warehouse operators plan labor, manage and incentivize employee performance, understand operational costs and monitor performance while work is taking place.
The company says this approach can help supervisors identify operational problems earlier instead of waiting until the end of a shift to understand what went wrong. “Warehouses generate more data than ever,” said Glynn LoPresti, co-founder and CEO of Takt, explaining that operators still need better ways to see when performance is moving off track.
Funding Will Support Product Expansion
Takt plans to use the new capital to expand its platform and strengthen its connections with other warehouse technologies.
The company will invest in deeper integrations with warehouse management systems, robotics and material-handling systems. It also plans to expand into areas such as order orchestration, resource scheduling and engineering tools.
The funding will also support the development of TaktAI agents and help the company expand its AI and automation capabilities. Takt plans to support customers as they grow their warehouse operations internationally, including expansion into markets such as the United Kingdom, the European Union, and Asia-Pacific.
Takt Already Works With Large Warehouse Networks
Takt has been expanding its customer base and partnerships in the warehouse and logistics sector. One example is Kenco, which has deployed Takt across 19 distribution centers and plans to extend the technology to another 30 centers. The companies announced their partnership in February 2026.
Takt has also partnered with Datex to connect its labor management technology with Datex’s warehouse management system. The goal is to give warehouse operators a more connected view of labor and operational performance.
Takt reports that its platform has also delivered measurable results for some customers. At a single-client consumer packaged goods site, Kenco reported a 15% reduction in average cost per pallet, representing $229,000 in annual savings. These figures are customer-reported results rather than independently verified figures.
Leadership and Next Steps
Takt was founded by Glynn LoPresti, Alex Rhea and Noah MacMichael. LoPresti serves as CEO, Rhea as CTO and MacMichael as CPO. Following the funding round, Sean Barkman, a partner at Ballast Point Partners, will join Takt’s board.
The $9.25 million Series A gives Takt additional resources to develop its warehouse intelligence platform, expand integrations and enter new markets. As warehouses continue to combine human workers with robotics and automated systems, Takt is positioning its technology around one central challenge: helping operators understand all parts of the operation in one place and act on that information before a problem affects the rest of the shift.
