The startup, founded by construction-tech veteran Slava Solonitsyn and automation engineer Anton Glance, applies Nvidia Omniverse–powered modeling to evaluate and optimize robotic operations at scale. 

Solonitsyn said the approach is intended to address historically low utilization rates that have hindered earlier attempts to automate construction tasks.

“By running thousands of Nvidia Omniverse–powered digital twin simulations before ever sending a robot to a job site, we can identify the workflows that deliver the highest impact and ensure viable economics from day one,” Solonitsyn said in the company’s announcement. 

The start-up's pre-seed funding  round, led by venture capitalist Tim Draper, will support Buildroid’s first U.S. activations under a shared-savings model in which the company receives 50% of net efficiency gains and guarantees performance metrics related to throughput and quality.

How the Simulation-First Platform Works

The initial commercial focus targets blockwork and partition-wall installation—segments Buildroid identifies as persistent bottlenecks for general contractors. For that first application, Glance said Buildroid has integrated two types of block-laying robots and an autonomous mobile robot for material handling. 

Buildroid’s block-laying robot positions a masonry unit during pilot testing, part of the company’s simulation-driven approach to coordinating multi-robot construction workflows.

Image courtesy of Buildroid

The block-laying systems can place units weighing up to 40 kg and build walls up to 4 m wide and 3 m tall, he said.

Buildroid software uses hierarchical task network planning for high-level sequencing and behavior trees for local task execution. The system performs iterative simulation cycles to validate plans based on cost, time or the number of robots. 

“Validation occurs through multiple iterations of scenarios aimed at achieving the desired optimization function,” Glance said in an email to ENR.

A central component of the platform is its BIM ingestion workflow. Buildroid has a plug-in for Autodesk Revit that converts models into OpenUSD format along with a YAML sequencing file and supplemental data. 

Glance said the company can operate from LOD300 BIM inputs but typically increases detail to LOD400 or LOD500 in the simulation, adding physical properties, textures and material attributes to better reflect field conditions. Once deployed, the system relies on a persistent digital twin to manage schedule changes and robot availability. 

“If a robot goes offline or conditions on the jobsite change, the digital twin automatically updates the plan and redistributes tasks to keep the project moving with minimal downtime,” Glance said.

The UAE pilots provided the company’s first real-world demonstrations. ALEC, one of the region’s largest contractors, confirmed active use of the technology. 

“We are piloting Buildroid’s robotic block-laying system on one of our sites,” said Imad Itani, head of innovation at ALEC. He added that the firm intends to use Buildroid’s BIM-based simulation tools to test robotic workflows virtually and reduce risks before on-site deployment.

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Solonitsyn said the regulatory environment in the UAE enabled rapid iteration during development, but U.S. rollouts will require more structured pathways due to state-level licensing and compliance requirements. 

“Once we have matured our systems enough, we will launch in the geographies where we have major GC partnerships,” he said.

Buildroid describes its platform as hardware-agnostic and says it supports more than 40 robot types, with plans to open the system to additional manufacturers. The company is collaborating with vendors to build digital twins of plastering, concrete leveling, concrete polishing and painting robots for future integrations. 

Glance said robots with higher autonomy levels integrate most easily, but Buildroid works with less advanced machines to improve their performance where needed.

Solonitsyn said the company views blockwork as the entry point to a broader roadmap of multi-robot workflows across interior fit-out and, eventually, larger segments of the construction lifecycle. 

“The goal is widespread adoption to boost productivity and operational efficiency in construction worldwide,” he said.