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Solutions · 04 · Industrial, Logistics & Smart Factory

The line cannot stop for data collection.

Manufacturers, warehouses and ports automating the flexible, high-mix work that fixed automation was never able to handle.

site CAD USD · SKUs DIGITAL TWIN AMR TRAIN policy the real line line changes · re-train against the twin
The twin is built from the CAD you already have, and every line change re-enters it instead of stopping production.

The problem

Traditional automation pays off when the part, the pose and the path never change. The work that is left over — mixed-SKU depalletising, cable routing, screw fastening on a non-standard fixture, picking something soft or transparent — changes constantly, and every site is laid out differently. You cannot halt a line for months of data collection, and a policy trained at one facility rarely survives the move to the next.

How the loop runs here

Generate

A digital twin of the actual site — CAD of the cell, the real SKUs, the real lighting — becomes the source of training data, built without touching the production line.

Train

Manipulation and navigation policies trained against that twin, then hardened with domain randomisation so they survive the gap between the model of the site and the site.

Validate

Full-shift simulated runs and AMR fleet behaviour before a robot is installed, including the failure modes that only appear when several robots share a floor.

Data in
Facility CAD / USD, SKU geometry, cycle-time targets, existing cell layouts
Model families
Manipulation policies, navigation stacks, open robot foundation models
Simulation
Site digital twins, Newton physics for contact-rich assembly, AMR fleet simulation
Deployment target
On-robot and edge compute inside the facility

What we provide

  • Project-shaped capacity: a burst per site or product line, then a steady trickle
  • Digital-twin generation from the CAD you already have
  • Re-training runs when the line changes, without rebuilding from scratch
  • Results that transfer between sites rather than starting over at each one

Industry context

The humanoid robot market is projected to reach US$38 billion by 2035 — more than a sixfold increase over previous forecasts — and the industrial floor is where most of those units are aimed.

Source: NVIDIA Blog

Contact

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Tell us what you're building. Our team will reply within 3 business days.

Email

sales@nexinfra.ai

Office

Wisma Tamara, 7th Floor, Suite 701, Jalan Jenderal Sudirman Kav. 24, Karet, Setiabudi, South Jakarta 12920, Indonesia