Industrial data infrastructure

Process-contextualized data from the real world

The last 1% of training data is 99% of your deployment risk.
We capture what lab-trained models can't see: factories, refineries, and facilities that robots need to master.
$2.6B+
Raised by frontier robotics labs in 2025
0.1%
Of training data from industrial environments
$50B+
Industrial automation market

Frontier labs have trained robots on millions of hours of household video. They can fold laundry and load dishwashers. But the industrial environments where robots are needed most remain a data desert.

Chemical plants, oil refineries, fabrication yards. Hazardous, regulated, and physically inaccessible. The generic data pipeline doesn't reach them.

Three layers of industrial intelligence

Not just video. Multi-modal data synced with the operational context of the facility.

01 / Capture

Raw Sensing

High-fidelity multi-modal capture
  • RGB-D video (egocentric + environmental)
  • Body pose and skeletal joint tracking
  • Hand detection and gesture recognition
  • Frame-accurate semantic action labels
02 / Enrich

Sensor Fusion

Layered telemetry for training signal
  • IMU and depth streams (RealSense)
  • Motion dynamics and orientation
  • Tool and equipment instrumentation
  • Process telemetry (ERP/MES sync)
03 / Contextualize

Intelligence Layer

What no other vendor provides
  • State-action pair generation
  • Process-contextualized annotations
  • Simulation-ready formatting
  • Robot-transferable demonstrations

Access and context.
Both are moats.

The Physical Moat

We go where others can't

Existing data vendors recruit in homes, kitchens, and offices. We embed directly in chemical plants, oil refineries, and heavy fabrication facilities through industrial partner relationships built over years of enterprise sales.

The Intelligence Moat

Operational context, not just pixels

Every dataset we capture is synced with the facility's ERP and MES systems, environmental sensors, and real-time process telemetry. This creates a "context-aware" dataset that a video labelling firm can never replicate.

Generic Vendors
Environment
Homes, kitchens, offices
Data
Egocentric video
Context
Video frame labels
Access
Open recruitment
Trekion
Environment
Chemical plants, refineries, fabrication yards
Data
Multi-modal + operational telemetry
Context
ERP/MES-synced process metadata
Access
Industrial partner network

From facility to foundation model

A pipeline that turns industrial workflows into robot-ready training data.

01
Partner
We embed in target industrial environments through existing facility relationships.
02
Capture
Off-the-shelf sensor rigs deployed by trained operators across the workflow.
03
Contextualize
Real-time telemetry synced with facility ERP/MES and environmental sensors.
04
Deliver
Simulation-ready, robot-transferable datasets in your preferred format.

Environments that matter most

We focus on the hazardous and regulated industrial environments where the data gap is widest.

Chemicals and Hazmat

Manipulation data from environments rated for explosive atmospheres. Extreme labor scarcity meets genuine physical danger.

$500 - $2,000 / hr data value

Oil and Gas Inspection

Structured inspection workflows with full operational context. Buyers already investing hundreds of millions in robot training.

Validated $600M+ buyer spend

Heavy Industry

Complex fabrication and assembly processes across high-entropy environments where generalization matters most.

Critical data complexity

The factory floor is the last frontier of AI training data.

If you're building robots for industrial environments, or operating the facilities they'll work in, let's talk.

Talk to Us