NERO DEV. Build a Dataset

The data infrastructure
for physical AI

Nero captures real work in real environments and turns it into structured training data for robotics and embodied AI.

Purpose-built hardware  ·  Distributed collection  ·  Model-ready data

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The Problem

AI learned language from the internet.
Robots need the physical world.

The actions robots need to understand happen inside warehouses, kitchens, workshops, stores, construction sites and thousands of other environments that were never recorded as machine-learning datasets. Nero builds the infrastructure to capture them.

Real work Nero Physical AI

The Network

Real work. Captured at scale.

Nero deploys capture systems into operating businesses instead of staging demonstrations in a lab.

Sites Workers Shifts Tasks Hours Datasets

2027 Collection Target

240

live collection sites

2027 Collection Target

300,000

cumulative hours captured

Building toward these figures by the end of 2027 — not current totals.

Capture Systems

The dataset starts at the sensor.

Different models need different observations. Nero designs its own capture hardware so collection architecture can be changed around the requirements of the dataset, instead of forcing every customer into the same sensor configuration.

Nero Mono Cap Cam — single-lens egocentric camera unit

Mono Cap Cam

High-volume first-person capture.

Nero's standard monocular egocentric capture platform for scalable human demonstration and real-world perception datasets.

Explore Mono Cap Cam
Nero Stereo Cap Cam — dual-lens egocentric capture unit

Stereo Cap Cam

Egocentric capture with spatial context.

Synchronized stereo vision designed for datasets that need depth estimation, geometric understanding, hand-object spatial relationships and 3D scene reconstruction.

Explore Stereo Cap Cam

Custom Programs

Your model defines the sensor stack.

Some programs need monocular RGB. Others need stereo vision, depth, inertial measurements, a wider camera baseline or synchronized observations from multiple viewpoints. Nero can engineer a capture configuration around the client's collection specification and deploy it through the same data infrastructure.

  • RGB
  • Stereo
  • IMU
  • Audio
  • LiDAR
  • Multi-camera
  • Custom sensor

Available custom program configurations. Not every configuration is currently deployed on every vertical.

The Data Engine

From real work to model-ready data.

  1. 01

    Capture

    Real tasks, real environments, Nero hardware.

  2. 02

    Ingest

    Encryption, integrity checks, sensor synchronization, dataset indexing.

  3. 03

    Process

    Calibration, frame extraction, quality filtering, redaction where specified.

  4. 04

    Enrich

    Tracking, segmentation, depth, pose, actions, interactions, language.

  5. 05

    Validate

    Automated QA, human QA where specified, schema validation, coverage analysis.

  6. 06

    Deliver

    Client schema, versioned datasets, API / object storage / batch, continuous feed.

See the full Data Engine

Commercial Models

Instead of buying a static dataset, connect your training pipeline to the physical world.

01

Dataset License

Non-exclusive access to a Nero dataset.

02

Exclusive Dataset

A collection program produced for one client with agreed exclusivity.

03

Continuous Data

An ongoing stream of newly captured and processed real-world data to an agreed specification.

Build the dataset your model actually needs.

Build a Dataset