Profile
Monumental is an Amsterdam-based construction technology company that develops and deploys on-site robotics to automate masonry and building processes. Founded in 2021 by serial entrepreneurs Salar al Khafaji (CEO) and Sebastiaan Visser (CTO), Monumental focuses on making construction software-defined and largely autonomous. The company’s mission is to enable beautiful, bespoke buildings to be completed within a single day with minimal labor, addressing chronic labor shortages, rising costs, safety issues, and the slow pace of traditional construction.
Monumental has raised $25 million in funding from leading investors including Plural, Hummingbird, Northzone, Foundamental, and NP-Hard. The company employs approximately 70–79 people and operates a hands-on office in the Plantage district of central Amsterdam, equipped with an in-house workshop and dedicated robot testing facility. Monumental deliberately runs as an in-office, non-hybrid company to accelerate iteration on its vertically integrated hardware and software stack.
At the core of Monumental’s offerings are fleets of small, electric autonomous ground vehicles (AGVs) purpose-built for on-site bricklaying and masonry. These robot-based systems are compact, agile, and designed to move freely across rough construction terrain just like a human mason would. Equipped with advanced sensors, computer vision for sub-millimeter localization, and small cranes, the robots can lay bricks and apply mortar with high precision across most common masonry bonds and standard material sizes.
Monumental’s robots do not require large capital purchases or extensive training by customers. The company operates a bricklaying-as-a-service model, acting as a subcontractor that supplies the robotic crew, handles setup, and charges clients on a transparent per-thousand-bricks basis. Multiple robots can operate in parallel—Monumental has reported deploying up to 30 AGVs simultaneously on a single site. The robots work 24/7 when needed and integrate seamlessly with existing human crews without forcing major process changes.
The flagship software platform is called Atrium. This AI-powered operating system creates a digital twin of the construction site, orchestrates the robot fleet, automatically handles details such as expansion joints and bat boxes, and generates complete quality-assurance documentation. Monumental’s machine-vision-driven approach allows the robots to adapt when real-world conditions differ from BIM or CAD models.
These robot-based systems deliver several key advantages. Because they are fully electric, they produce zero on-site emissions and significantly less noise. Faster build times and the ability to run continuously help reduce overall project duration and construction costs. Safety improvements are central: Monumental aims to remove humans from some of the most dangerous tasks in an industry with tens of thousands of casualties globally each year. At the same time, the software-defined approach restores the possibility of intricate, beautiful, and custom artisan work without increasing labor requirements.
Monumental has already deployed its robots on numerous real-world projects across the Netherlands. Completed or ongoing work includes house facades, detached single-family homes, care homes, a hotel, an epilepsy and sleep medicine center, and multiple canal retaining walls (kademuren) in Amsterdam. The company is now expanding into the United Kingdom and has begun participating in initial UK projects.
Monumental differentiates itself from other construction automation efforts by keeping everything on-site rather than relying on off-site prefabrication. The robots are small enough to pass through doorways and work in tight spaces, making them suitable for both residential and commercial buildings. By focusing first on masonry while building scalable fleet-coordination software, Monumental plans to expand the capabilities of its robot platform to additional construction tasks over time.
Map
Sorry, no records were found. Please adjust your search criteria and try again.
Sorry, unable to load the Maps API.





