Jason Tielve and Omar Hafez on How FireDesign.ai Is Using AI to Automate Fire Sprinkler Design.
Fire sprinkler design is slow, manual, and bottlenecked by a shortage of experienced engineers. In a JustAINews interview, founder Jason Tielve and Chief AI Officer Omar Hafez break down how AI reads architectural plans, generates code-compliant layouts, and where human oversight remains non-negotiable.
FireDesign.ai founder and CEO Jason Tielve and Chief AI Officer Omar Hafez sat down with JustAINews to explain how the platform applies AI to one of construction's most stubborn bottlenecks — fire sprinkler design — without ever letting automation become the final decision-maker for life safety.
A few of the threads from the conversation:
- The bottleneck is people, not process. As Tielve puts it, "the demand for fire protection continues to grow, but the number of experienced designers isn't growing at the same pace." Engineers spend too many hours on repetitive drafting instead of applying judgment where it matters.
- AI reads the plans; engineering rules govern the output. Hafez frames the split clearly: "AI handles understanding the plans and making sense of unstructured data, while the engineering logic ensures the final output follows established fire protection standards." Deterministic, NFPA-based rules do the code work.
- Fail-closed by design. The system is deliberately conservative — ambiguity triggers manual review rather than an automated assumption. A confidence score drives the workflow, so only high-confidence plans move through automated design.
- Augmentation, not replacement. "We're not trying to replace designers," Tielve says. "We're giving them a tool that eliminates repetitive work." Licensed engineer review stays mandatory for certification, water supply decisions, and AHJ approval.
- Code compliance comes first. In Tielve's words, "Nothing else matters if the system doesn't meet code" — and "AI should assist professionals, not replace professional responsibility."
- What's next. The long-term roadmap extends the same AI-assisted, rules-governed approach beyond fire sprinklers to the broader MEP stack — plumbing, mechanical, and electrical.