The Physical AI Data Platform

Real-world data for real-world AI.

ProData provides accurate, fresh, and production-ready datasets for Physical AI by collecting real-world data using proprietary hardware, automated pipelines, and direct access to environments.

Physical AI Data Visualization

The Problem

Physical AI models fail because of data.

For robotics, autonomy, and industrial AI, bad data means unusable models.

Synthetic data doesn't generalize

Simulations lack the chaos and noise of the real world.

Stale datasets

Open datasets don't reflect current, changing environments.

Messy sensor data

Unstructured logs take months to clean before training.

No real-world access

Developers lack access to factories and fields for collection.

Slow pipelines

Manual processing blocks iteration speed for months.

Our Solution

The infrastructure layer for Physical AI.

Collect

Real-world data from the field using proprietary hardware.

Automate

Automated acquisition pipelines and sensor sync.

Process

Clean, structure, label, and version datasets automatically.

Deliver

Training-ready data delivered fast to your models.

What sets ProData apart.

We don't just scrape the web. We build hardware, deploy to the edge, and capture ground truth.

Proprietary Data-Collection Hardware

We build purpose-designed hardware for Vision (RGB, depth), Motion, and Environmental sensing. This lets us capture high-signal, synchronized data—not generic logs.

Access to Real-World Environments

Direct access to factories, facilities, roads, and warehouses. We don't wait for customers to 'find data.' We have deployment-ready rigs and repeatable setups.

Automated Acquisition & Prep

End-to-end automation for sensor sync, metadata, alignment, and labeling. We turn months of cleaning into days of training.

Fresh, Accurate, Model-Ready

Continuously updated datasets aligned with actual deployment conditions to improve model convergence and robustness.

Who We Serve

  • Robotics & Manipulation
  • Autonomous Systems
  • Industrial Automation
  • Edge AI & Embodied Intelligence
  • Simulation-to-Real Transfer
  • Safety-Critical AI Systems

Why Now?

Physical AI is exploding, but models are advancing faster than real-world data pipelines.

Synthetic data alone is hitting limits. Hardware + Data + Automation is the missing stack.

Everyone is building models. Almost no one is solving real-world data at scale.