nodal layout framework

First ever portable motion capture system.
Deploy anywhere at anytime

For athletes, coaches, creators, artists, researchers. More affordable and easy to use.

Sub 5ms
Synchronization
Can support more than 20 cameras
120 FPS
Global Shutter
20x
More affordable
than Vicon or Qualysis
<5 min
Setup time
Plug and capture
Industries
Built for your workflow
🤖

Robotics & AI Training Data

Ground-truth data

High-fidelity multi-camera pose datasets for imitation learning, sim-to-real validation, and perception model training — captured, not simulated.

🔬

Clinical & Research

Motion data

Lab-grade accuracy with on-device processing — no patient data leaves your facility. Built for IRB-friendly clinical studies and biomechanics research.

🏋️

Sports Performance

Biomechanics

Biomechanical analysis for coaching, injury prevention, and athlete development — field or gym.

🎬

VFX

Markerless mocap

Studio-quality markerless skeletal tracking. Drop into existing pipelines without a hardware overhaul.

Proof, not promises
Watch the tracking, not a claim about it

Pulled directly from an internal QA capture: four synced cameras tracking a full lift in a real gym, with per-camera reprojection error overlaid live and the triangulated 3D skeleton reconstructed alongside it.

4-camera array Full-body + barbell tracked together Live 3D triangulation Real gym, no markers

From an internal capture session — swap in your validated benchmark numbers once available.

Applications
Built on the same tracking core
Live tracking capture
Sports · Weightlifting

Bar path & lift tracking

Bar path, bar velocity, range of motion, and rep counting — captured automatically from a multi-camera rig, no markers or sensors on the athlete or bar.

Barbell endpoint model Full-body keypoints Rep auto-count
Sample output · synthetic data
Sports · Basketball

Shot tracking & zone efficiency

Every shot located, scored, and zoned in real time — makes, misses, and efficiency by court location, built from the same camera-and-keypoint pipeline.

Ball + rim detection Zone classification Live heat mapping
Custom models

Every application runs on a model trained for that exact problem

Barbell + plate endpoints, sport-specific joint sets, ball and rim detection — we build and tune the keypoint and object models behind each application rather than relying on a generic off-the-shelf pose model. Tracking a sport or workflow that isn't listed here? That's a conversation we want to have.

Software
One pipeline, from camera to clean 3D data
1
Process UI showing a recording session queued for cloud 3D pose estimation A10G cloud processing
Session Processing

Three clicks to a cloud GPU

Point it at a recording session, confirm anchors, hit upload. 3D pose estimation runs on a cloud A10G GPU — no local GPU, no pipeline to babysit.

2
Relabeling UI showing a worklist of flagged frames with per-camera reprojection error QA worklist
Relabelling

Fix exactly what the model missed

Frames with high reprojection error are queued automatically. Correct a joint once, across every camera view, and the fix propagates through the clip.

3
Visual skeleton UI playing back the reconstructed 3D skeleton overlaid on the source footage Skeleton overlay
Visuals

Confirm the fix before moving on

Play the corrected 3D skeleton back over the original footage, frame by frame, to verify tracking is clean before it's used downstream.

↻ Steps 2 and 3 repeat, clip by clip, until reprojection error is low enough to trust

Coming next

Gait analysis report

Stride length, joint angles, symmetry, and more — generated automatically once a clip's tracking has been verified through the pipeline above.

🔒

Private

Country-based servers, for example UK-based for UK deployments — compliant with the UK Data Protection Act 2018.

🛡️

Secure

Cloud video purged weekly — most processing runs offline, on-device.

Easy

Automated QA flags — clean 3D data, no computer vision background required.

About
Why Nodal

Enterprise 3D pose estimation systems cost hundreds of thousands of dollars and take weeks to set up. We built nodal because we've seen firsthand — working at Sony and Google — that the core technology is mature enough to be made accessible. Our mission is to put professional-grade computer vision tools in the hands of every sports team, indie studio, and factory floor.

Founders
The Founding Team
Hansen, Co-Founder

Hansen

Co-Founder · Hardware

Leads hardware design and the product vision for nodal's camera rigs. Previously a hardware engineer at Sony, working on camera and imaging systems. Sets the direction for sensor integration, rig design, and where the hardware goes next.

Kyle, Co-Founder

Kyle

Co-Founder · Software

Leads software, model training, and visual output at nodal. Previously worked at Google. Builds and trains the keypoint and tracking models behind each application, plus the dashboards and visualizations that turn raw tracking data into something usable.

Contact
Get in touch