EquipGuard AI comes out of real operating experience, not a lab — from mine sites to autonomous machine design.
EquipGuard AI was founded to close a gap seen firsthand across mining sites in Türkiye, Iran, and the Middle East: heavy equipment fails without warning, and most fleets still run on reactive maintenance.
We build fleet intelligence software for the people who actually operate and maintain heavy machinery — not generic enterprise dashboards, but tools shaped by real pit-floor experience.
Give every fleet operator the visibility to prevent failure before it happens.
A standard where unplanned equipment downtime is the exception, not the norm.
Every feature is grounded in real mining and equipment operations, not assumptions.
EquipGuard AI isn't a standalone tool — it's one of four products built inside MineVision AI, the Land division of Mine Vision Ecosystem. Every product in the family shares the same engineering standards, the same field-tested foundations, and the same team.
Ramin is a senior mining and digital infrastructure executive based in Istanbul, with over two decades of experience in mining, autonomous systems, and deep technology across Türkiye, Iran, and the Middle East.
He is a PhD candidate in Mineral Processing at İstanbul Üniversitesi–Cerrahpaşa, and holds an Executive MBA and MSc from METU. Alongside EquipGuard AI, he founded MineVisionAI, DeepVisionAI, and MicroDrill AI.
Developed at METU, the KSP-32 is a remote-controlled roadheader robot for tunneling and excavation — the research project that anchors EquipGuard AI's understanding of how heavy mining equipment actually fails and needs to be maintained.
KSP-32 remains Ramin's flagship research project and a direct link between academic robotics research and field-ready fleet intelligence.
See how two decades of field experience became a fleet intelligence platform.
Request a Demo
