The Robotics Model Built for Messy Warehouses

TorqueFlow is a physics-reasoning world model built for high-throughput operations in messy, dynamic warehouse environments.

Isometric warehouse map showing TorqueFlow use case locations
01
Container Loading & Unloading
Container loading and unloading
Reasons about 3D stability, occlusions and reachability in complex box stacks.
02
Humanoid Material Handling
Humanoid material handling
Long-horizon adaptable reasoning across a variety of tasks.
03
Kitting & Repackaging
Kitting and repackaging
Contact-rich and multi-step manipulation policies.
04
Mixed-SKU Sorting
Mixed-SKU sorting
Reflective film, polybags, items that shift on the belt. ≤30ms per pick decision.
05
QA & Exception Routing
QA and exception routing
Anomalies flagged, classified, and routed while the line keeps running at speed.
Active use case
03 · Kitting & Repackaging
Contact-rich and multi-step manipulation policies.
01
Container Loading & Unloading
02
Humanoid Multi-Task Deployment
03
Kitting & Repackaging
04
Mixed-SKU Sorting
05
QA & Exception Routing

Container Loading & Unloading

Container and trailer unloading is one of the highest-variability manipulation tasks in logistics. Human loaders pack trailers under time pressure. Boxes arrive at angles from 5° to nearly horizontal. Stack heights vary. Labels face every direction. TorqueFlow reasons about the 3D layout of each load as it encounters it, identifying box pose, estimating stability, and sequencing picks that maintain structural integrity across the stack. It works through specular tape, partial occlusion, and unlabeled cartons.

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Humanoid Multi-Task Deployment

The challenge in warehouse automation is operational variability. Warehouses were designed around human adaptability, with workers moving between stations, retrieving inventory, replenishing materials, and handling exceptions as needs change. One shared physical reasoning model transfers across those activities. TorqueFlow understands grasping, contact, stability, and object behavior, adapting to new tasks with minimal data collection. Operators extend a single model across a growing range of warehouse activities.

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Kitting & Repackaging

Kitting and custom order assembly require a robot to work through sequences that change with every order. Item configurations vary. Packaging is often deformable. The robot needs to reason about what it's holding, not just where it is. TorqueFlow handles the contact-rich manipulation that kitting demands such as deformable bags, variable bin layouts, and multi-step assembly sequences across changing order configurations.

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Mixed-SKU Sorting

Mixed-SKU sorting demands speed and accuracy across items that vary in size, weight, surface finish, and packaging type. Reflective packaging, flexible polybags, and items that shift on the belt are what your line runs on every day. Specular surfaces, soft packaging deformation, and partially occluded items run at full line speed, with TorqueFlow outputting pick-and-place commands in ≤30ms, accuracy holding on the hard cases.

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QA & Exception Routing

QA and exception handling require identifying anomalies, classifying failures, and routing items without slowing production throughput. Packaging, lighting conditions, and product configurations vary across operations. Visual understanding and physical reasoning run together in TorqueFlow, supporting automated inspection and pick-and-divert workflows that identify dimensional deviations, packaging issues, and handling exceptions at line speed.

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<30ms
Latency that maximizes throughput
~50
Examples only, deploy in weeks
99.9%
Accuracy on production warehouse lines

Deploys on the Robots You Already Run

TorqueFlow deploys across industrial manipulators, trailer-entry robots, mobile manipulators, cobots, dexterous robotic systems, delta robots, SCARAs, inspection stations, gantry systems, and AMRs.

Runs On
NVIDIA Orin
NVIDIA Thor
RTX GPUs
Custom edge SoCs

Physics reasoning built for warehouse conditions

TorqueFlow combines perception, 3D spatial reasoning, and physical understanding into a world model of the floor it operates on, tracking how objects behave and interact as work happens. That model is what carries across new SKUs, layouts, and workflows with a fraction of the task-specific data.

Modular architecture diagram

Modular Architecture

Run TorqueFlow as a complete stack, or integrate single components: perception, physical reasoning, or task planning. Each one tunes to a deployment on its own, without retraining the full model.

Physics reasoning diagram

Physics Reasoning

A world model of the cell that holds geometry, contact, and material behavior together, from stack stability to deformable packaging, and reasons through the interaction before the robot commits to a motion.

Edge hardware icon

Runs at the Edge

≤30ms inference on edge hardware next to the line, so cell throughput stays independent of network conditions. No cloud dependency.

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Tell us what you're running and the workflow you want to crack — we'll deliver a model tuned to your deployment and our team will reach out within one business day.

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