Automation has barely begun in India's component plants.
The parts vary, so the work stays manual. Qnion builds the physical AI that lets a robot pick parts it was never taught.
Demand is rising, and the robot base is thin.
Every change to a taught cell costs weeks, fixtures and a specialist.
Robots pay back only on high-volume parts. Every other station stays manual.
Each new part takes weeks.
Expert programming, calibration and fixture design, for every part or layout change.
NVIDIA and Workr, robot retasking case study, 2025
The robot is the smallest cost.
Robot hardware is a quarter of a cell's cost. Integration and peripherals make up the rest.
BCG, The Robotics Revolution, 2015
Only a specialist can program it.
Pendants, robot languages and coordinate frames shut out the process engineer.
A Qnion robot is told what the part is, not where it is.
Each of those costs exists because a taught robot is told where the part is. Qnion removes the cause.
Each part in 3D
It from its CAD model
Its own motion
One part library, any robot
The cell runs in our lab, and we are seeking pilots.
The cell runs in our lab.
Live part tracking, pick and place zones, part checking and cycle replay.
Backed by Siddha Perfect Systems.
600+ conveyor and handling installations over 20+ years in India's forging plants.
Prototype, seeking pilots.
Qnion is a DPIIT-recognised startup. We are looking for pilot partners in forging and casting plants.
Qnion builds its AI and controllers in Pune.
Prabhakar Naik
Founder and CEOMS, Robotics and Control, Columbia UniversityMechanical Design Engineer (Mobility), Matic RoboticsAtharva Joshi
Electrical Engineer
Abhishek Kattimani
Mechanical Engineer
Advisors: Ravindra Natu, former Managing Director, Amitron Engineering. Manoj P. Naik, CEO, Siddha Perfect Systems. Mangesh P. Naik, Managing Director, Siddha Perfect Systems.
Start with a visit to the lab.
Watch the cell pick parts it was never taught, in Bhosari, Pune. Then we talk.