FireDesign.ai founders Jason Tielve and Omar Hafez were recently interviewed by JustAINews, where they spoke with co-founder Genaro Palma about how the platform uses AI to streamline one of construction's most manual, time-intensive workflows — fire sprinkler system design.
A few of the threads they pull on in the interview:
- The bottleneck. Fire sprinkler design is slowed by labor shortages and repetitive manual work, even though code requirements stay largely consistent from project to project.
- How it works. The AI interprets building geometry from architectural plans using computer vision and geometric reasoning, while a deterministic rules engine enforces NFPA compliance. As Hafez puts it, "AI is responsible for reading plans... but making code compliance decisions is handled separately."
- Human oversight stays central. Tielve emphasizes that "software should support that judgment, not replace it." Licensed engineers review every output before certification.
- Quality assurance. Each new feature is validated against benchmark projects and deterministic rule checks before it reaches production users.
- What's next. Expanding the same hybrid AI-plus-rules approach to other MEP disciplines — plumbing, mechanical, and electrical.