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Athla Labs / Physical AI

Robots learn from the real world. Athla Labs captures how industrial work is actually done and turns it into structured data for physical AI.

Industrial access network

Industrial access, already in place

Athla Labs works directly with industrial operators across Indonesia to create access to real-world workflows for physical AI data collection.

Participation in individual collection projects remains subject to worker consent, site approval and project requirements.

Collection partners

Collection Network

Our partner network provides access to real industrial environments and operational workflows relevant to physical AI. All partners have signed an MOU with us.

Industrial & technical partners

Industrial & Technical Network

Some partners support the network rather than providing recording sites. They review collection plans and introduce us to manufacturers and automation specialists. These relationships help us understand industrial workflows and plan collections that reflect how work is really done.

Environments

What We Can Capture

Each environment offers repeatable physical work. Each task carries signals that robotics and physical AI models find hard to learn from internet data.

How we work

From the factory floor to AI-ready data

Every dataset follows the same path, so the people training models can trust what they receive.

  1. 01

    Capture

    We record egocentric footage from workers in real industrial environments, with the consent of the people and sites involved.

  2. 02

    Structure

    Captured data can be synchronised, quality-controlled, structured and annotated to each buyer’s required schema, so the scope matches what the model needs.

  3. 03

    Deliver

    We deliver datasets to physical AI and robotics teams, and work with them on the coverage and tasks their models need next.

    Depending on scope, delivery can include

    • Raw video
    • Sensor / IMU data
    • Metadata
    • Quality-controlled datasets
    • Buyer-specified annotations
    • Structured robotics datasets

What we stand for

Principles

Real environments

Data from actual working sites, not staged scenes, because that is where robots will have to perform.

Structured by default

Clear schemas and documentation from the start, so teams spend their time training, not preparing.

Built with partners

We work alongside sites, workers and research teams, and keep consent and privacy at the centre of collection.

Tell us the task your model needs.

We work backward from your task requirements to identify suitable environments, workflows and collection specifications.