Construction Tech Startup Xpanner Raises $18 Million as demand for AI-powered infrastructure solutions

Stella Young
4 Min Read
Modernconstruction360

Construction automation startup Xpanner has secured $18 million in Series B bridge funding as demand for AI-powered infrastructure solutions continues to grow across the United States. The company plans to use the fresh capital to expand its subscription-based automation services for large construction and energy projects, including solar farms, battery storage facilities, and AI data centers.

The funding round was led by Korea Investment Partners, with continued participation from KB Investment Co. Following the latest investment, Xpanner’s total funding has reached $38 million since the company was founded in 2020. The company currently operates from Santa Fe Springs, California, after relocating its headquarters from South Korea to the U.S. in 2023.

Xpanner focuses on construction robotics and physical AI technology designed to automate heavy equipment operations without requiring contractors to replace their existing machinery fleets. Its approach comes at a time when the U.S. construction industry is facing labor shortages, rising project costs, and growing pressure to complete large infrastructure developments faster.

Xpanner Expands Automation-as-a-Service Model

Instead of building entirely new autonomous machines, Xpanner retrofits existing heavy equipment using its proprietary X1 Kit. The system combines hardware and software to automate construction tasks such as piling, grading, trenching, and material handling.

The company delivers these capabilities through an Automation-as-a-Service (AaaS) model. Contractors purchase software licenses and automation services through a cloud-based platform, allowing them to add autonomous features to existing equipment without making large upfront investments in new machinery.

According to the company, the model helps construction firms convert heavy capital expenses into predictable operating costs while improving productivity on job sites.

Ryan Park, co-founder, chief financial officer, and chief strategy officer at Xpanner, said the latest funding will help accelerate the company’s physical AI solutions and support the expansion of its subscription-based automation platform in the construction sector.

Revenue Growth Driven by Infrastructure Demand

Xpanner reported strong financial growth over the last three years as demand increased for automation solutions in energy and infrastructure construction projects.

The company said revenue grew from $3 million in 2023 to $7 million in 2024 and reached $21 million in 2025. Xpanner also reported $8 million in revenue and $1 million in EBIT during the first quarter of 2026.

The company has secured enterprise contracts with infrastructure and engineering firms, including Mortenson, Black & Veatch, and Qcells. Much of the recent demand has come from utility-scale solar projects, battery energy storage developments, and data center construction linked to the rapid expansion of generative AI technologies.

Industry observers have noted growing investor interest in physical AI companies that combine robotics, automation, and machine learning for real-world industrial applications. Xpanner’s software-focused strategy has also attracted attention because it avoids many of the manufacturing and logistics challenges faced by traditional hardware robotics companies.

Company Plans Further Expansion

Xpanner said the new funding will be used to develop next-generation automation hardware, improve its machine-learning engineering systems, and expand industrial data infrastructure to support high-growth energy projects across the U.S. market.

The company also plans to continue scaling its subscription-only business strategy and is targeting a $60 million annual recurring revenue run rate by the end of 2026.

Investors backing the company believe Xpanner’s retrofit-based automation model positions it well in the growing construction technology market, where contractors are increasingly looking for cost-effective ways to improve productivity and reduce labor dependency.

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