Data multiplication · physical AI

Capture once.
Train every condition.

Syntheta helps physical-AI teams get more useful training experience from every real capture. Turn factory, robot, drone, and sensor footage into trusted data for the situations that are hardest to collect.

Request beta access See the contact sheet →

Original capture · clip-01-v2 · 10s 1072 × 480

Why this matters

Capture is the bottleneck.

5–30 min

of real capture to start a dataset run

Multi-class

industrial taxonomy with masks and boxes

Validated

variants with provenance and quality gates

Real-world capture is slow and rarely covers every operating condition. Syntheta takes the data you already have and creates useful, labeled variations for low light, motion, occlusion, new viewpoints, and difficult edge cases. The result stays tied to the original scene, so your team can inspect it, trust it, and put it to work.

How it works

One capture. A larger training set.

Bring a real captureFactory, robot, drone, or synchronized sensor data.

Define the conditionsChoose lighting, motion, occlusion, views, and sensor variation.

Generate and validateProduce new samples while carrying labels and provenance forward.

Train on what mattersExport a ready dataset and measure utility on held-out real data.

Contact sheet

From one real capture

Inspect the transformation chain: real capture, restoration, controlled generation, spatial reconstruction, and world-model evaluation.

Last validated run

Numbers, not adjectives

500

automated tests passing in the current build

1 → many

real capture expanded into controlled training experience

RGB + depth

appearance and spatial outputs from aligned captures

Multi-step

world-model rollouts with motion and sensor state

YOLO / COCO

train-ready detection and segmentation exports

Real → real+

held-out evaluation for training-data utility

Fail closed

invalid labels and geometry stay out of exports

provenance contract across every modality

Built on

What's actually running

YOLOv8n-pose

NeuroDepth-T4 · EventCore V8.1

Geometry-conditioned generation

R2R mutation engine

YOLO / COCO dataset export

New viewpoints from real scenes

Future-state prediction for physical AI

Get early access.

Bring a real capture and your target classes. We return an expanded dataset, labels, provenance, and a training baseline.

Capture once.Train every condition.