We're Building the Decision Layer Construction Never Had.

Pavel has spent his entire career in construction — and he's convinced the industry is ready for a fundamental shift in how it makes decisions.

He started underground, literally. His first years were as a tunnel engineer, where he learned how construction projects actually get built — the complexity, the risk, and the gap between what gets planned in an office and what happens on a job site.

From there, Pavel moved into the business side of construction, taking on product and go-to-market roles that gave him a front-row seat to how firms grow, compete, and make strategic choices. As a Product Manager, he defined and led the development of an entirely new construction power tools category that grew into a $50M+ business. As a Regional Head of Marketing, he accelerated a Tools-as-a-Service offering across 11 countries — taking growth from 15% to a record-breaking 77% in a single year.

Across every role, one thing stayed constant: the decisions that shape a construction firm's success — which projects to bid, which to walk away from, which teams to deploy — rely heavily on hard-won experience. Pavel believes that experience deserves to be amplified with better analytical tools, so the same firms that build billion-dollar infrastructure can bring that same rigor to deciding what to build next.

At SiteScope, Pavel leads customer engagement and fundraising — translating 13+ years of construction experience into relationships with the general contractors who need better decision-making tools.

Gabriel has spent years studying a question most people in AI don't ask: where does this technology actually work — and where does it break down?

As a PhD student and researcher at MIT's Department of Electrical Engineering and Computer Science, Gabriel co-authored "The Computational Limits of Deep Learning" — a paper that became one of the most cited analyses of AI's sustainability challenges, with over 450 citations. The research showed that the AI industry's progress depends on unsustainable growth in computing power, and that the future belongs to methods that are computationally efficient and practically grounded.

That perspective shapes everything Gabriel builds. Before SiteScope, he developed intelligent tools to extract structured data from legal documents — turning messy, unstructured information into clean, usable datasets that improved government transparency and audit efficiency. It was the same kind of problem construction faces: valuable data locked in formats that no one can learn from.

At SiteScope, Gabriel leads product and development. He brings 6+ years of R&D experience in AI and software engineering — not to build the most complex system possible, but to build the one that actually works for the people using it. His goal is to take the research that's been sitting in academic papers and put it in the hands of pre-construction teams who can use it to make better decisions every day.