The Robo-Centric Data Foundry

Robo-Centric Data Foundry

Not by hand.

But automated.

Today, most robotics data is collected through teleoperation — a human operates a robot, one task at a time. It's slow, expensive, and capped at a 1:1 human-to-robot ratio. Generalizable physical AI stays bottlenecked by data scarcity.

Lili-o replaces human-dependent collection with an industrial-grade autonomous foundry. Powered by our One-Shot/Zero-Shot execution architecture, robots run 24/7, retry on failure, and generate synchronized, contact-rich episodes continuously — with minimal operators per run.

KitchenLiving roomBathroomLaundry roomBedroom
24/7
operation
50+
home environments
0
operators
Lili-o foundry environments
The missing layer

Tier 1 Robo-Centric data.

High-fidelity, cross-embodiment data generated directly by autonomous robots. It is the only data that scales models — and no one had found a way to produce it efficiently. Until now.

See how the three data tiers compare →
<4%

The “Perfect Run” flaw

Fewer than 4% of existing high-fidelity datasets contain failure or recovery episodes, and tactile data is nearly non-existent. Robots trained only on flawless trajectories fail the moment they meet minor real-world variation or unexpected slippage.

When a Lili-o robot fails an action, it automatically triggers autonomous recovery loops — capturing the rarest data in the industry: real physical failure and recovery.

Comparison

The market settled for trade-offs. We didn't.

SimulationHuman-CentricTéléopérationLili-o
Rich MetadataLowMediumHighHigh
Environment DiversityHighHighLowHigh
PriceMediumLowHighHigh
Cross-embodimentNoYesNoYes
ScalableHighMediumLowHigh
CompaniesLightwheel · NVIDIAScale · SenseiroboticTutor · Figure · AgibotLili-o

*EU AI Act compliant

The product

Synchronized multimodal tokens.

Every episode is an enterprise-ready, synchronized data stream built for direct injection into cutting-edge training pipelines. Force-torque and proprioceptive signals — absent from almost all public datasets — are first-class here.

01

RGB-D Video

Synchronized multi-view capture with aligned depth — 3D spatial structure and object tracking at every frame.

02

Tactile / Force-Torque

Contact forces at the end-effector. The signal almost no dataset has, and the one contact-rich policies need.

03

Proprioceptive Trajectory

Full closed-loop internal robot states mapped to hardware-agnostic Cartesian spaces. Retargeting included.

04

Labellisation

Pre-labeled task IDs, object classes, and success/failure logs. Zero downstream cleaning required.

Targeted Pipeline Ingestion

Access thousands of synchronized, real-world multimodal episodes tailored specifically to your token ingestion and model training specifications.

Turnkey Enterprise Bundling

Ready-to-train datasets built to package directly into enterprise cloud infrastructure (such as AWS) for immediate client deployment.

Outcomes

What design & cloud partners get.

Unprecedented Scale

Move past low-yield teleoperation to a continuous pipeline delivering multimodal episodes at a fractional marginal cost.

Out-of-Distribution Resilience

Feed your models the vital recovery loops needed to handle real-world chaos without collapsing.

Cross-Embodiment Versatility

Dataset outputs translate across completely different robot architectures — no embodiment-specific retraining.

Immediate Revenue Acceleration

Drastically reduce development and PoC deployment timelines, unlocking delayed ROI for Physical AI software and hardware.

Second channel

Real homes. Real people. Real tasks.

Our second collection channel sends instrumented participants into their own homes — kitchens, bathrooms, laundry rooms — wearing RGB-D cameras and haptic gloves, performing everyday household tasks as they naturally would.

This captures the environmental chaos, behavioral variance, and physical interaction that a controlled environment can never replicate. The mess on the counter. The wet dish. The awkward cabinet angle.

RGB-DTactile / hapticDiverse home layoutsNatural behaviorEU AI Act ✓
Kitchen
  • Dish washing
  • Meal prep
  • Appliance use
  • Counter cleaning
Living room
  • Object sorting
  • Table setting
  • Tidying
  • Vacuuming
Laundry room
  • Folding clothes
  • Loading washer
  • Ironing
  • Sorting laundry
Bathroom
  • Surface wiping
  • Bin handling
  • Towel folding
  • Cleaning fixtures

Ready to train on the data Physical AI has been missing?

Request access