Kilsar just secured $3.7M in seed funding. And no, this isn’t your average “AI startup raises money to build another chatbot” kind of story. This is about sweat, steel, and solving a very real, very old problem: how to keep critical know-how from disappearing the moment your best technician clocks out for the last time.
You ever try replacing a 30-year veteran with a PDF and some PowerPoint slides? It’s like trying to fix a jet engine with a YouTube tutorial and a prayer. Kilsar’s founders, Brendan Lawlor and Zach Casey, didn’t need a whiteboard session to figure that out. They saw the tribal knowledge gap firsthand while embedded in defense maintenance environments. And instead of treating it like a process problem, they built something with teeth.
The result? Orion. An AI-driven platform that doesn’t just record what the experts say, it learns how they work, why they improvise, and what they know instinctively after years on the job. Think of it like capturing the soul of maintenance, then turning it into something structured, searchable, and scalable across fleets, factories, and fuel plants.
With new capital from Lightbank, Cotulla Capital, ScaleWolf, and Techstars, Kilsar isn’t just staffing up, they’re sharpening the blade. More engineers, deeper AI capabilities, and faster deployment across aviation, energy, and infrastructure. And they’ve got real traction: a fresh partnership with the Aviation Institute of Maintenance, a Phase 1 SBIR with the US Air Force, and a clear signal that the market’s not just ready, it’s starving for this.
Let’s be real: maintenance isn’t sexy. But it is mission-critical. Every time an aircraft sits idle because someone didn’t know how to swap a component, a company bleeds money and time. Orion flips that equation, delivering step-by-step digital workflows, real-time AI assistance, and enriched content that actually replaces static manuals. We’re talking about operational continuity at a level that would make most CIOs weep with gratitude.
Brendan Lawlor and Zach Casey have done something few others in the AI world can claim: built a product that’s not only technically sound, but deeply necessary. And they’ve done it without gimmicks, just good tech solving hard problems.
