The European Financial Review · August 7, 2026
The Engineer Who Is Rewiring Industrial America
The European Financial Review profiles Omar Hafez and Think Big Technology, tracing a deliberate strategy of building domain-specific AI for regulated, documentation-heavy industries rather than broad consumer tools.
By The European Financial Review
The European Financial Review profiles Omar Hafez as an engineer who chose, deliberately, to point artificial intelligence at the least glamorous corners of the economy. He studied at the New Jersey Institute of Technology and came to the venture by way of financial technology and enterprise software, founding Think Big Technology in 2021.
The piece frames the company's strategy as a bet against the prevailing direction of the AI industry. Rather than building broad consumer applications, Think Big concentrates on what the article calls the most complex, risk-laden industries — construction, fire protection engineering, financial services, and digital identity — on the argument that these are the sectors where automation has the furthest to travel and the most to contribute.
That lag is not incidental. Industries bound by extensive documentation requirements and regulatory complexity have historically been slow to adopt digital tooling, precisely because generic software struggles with work that has to satisfy a code official as well as a client. The article positions domain-specific systems, built around the rules of a particular trade, as the response.
Six platforms are described as the current portfolio: FireDesign.ai, which converts building blueprints into fire protection plans; Poseidon, a project tracking system used by more than 500 contractors; Sprink AI, which assists with NFPA code compliance; Nexcard, a digital business card product; Stak, a budgeting application; and DateDash, a verified dating platform.
The throughline the profile draws is one of compounding domain knowledge — that the difficulty of these industries, usually treated as a reason to avoid them, is the reason the resulting software is hard to displace.
