Physical AI Data Infrastructure

The data
layer for physical
AI.

Teleoperation demonstrations, egocentric video, and precision annotation — delivered at scale. We build the training data that teaches robots how the real world works.

DXT-001 · REV A Physical AI
Data Station Spec
Station TypeBimanual Teleop
HardwareALOHA-Compatible
Output FormatLeRobot V2
Dataset Compat.ABC-130K
Cameras3-View Sync
Episodes / Day100+
QA Rate100%
Cost vs. US5× Lower
Pilot Lead Time2 Weeks
( 01 ) The Challenge

Physical AI is blocked
by real-world data.

Challenge 01
Demonstration data doesn't scale.

Foundation models for physical AI need thousands of task-specific human demonstrations. Collecting them in-house is slow, expensive, and a distraction from model development.

Challenge 02
Open datasets only go so far.

ABC-130K and similar open datasets are valuable baselines. But your robot needs data for your specific tasks, your specific environment. Generic data doesn't close that gap.

Challenge 03
Raw video is not enough.

Teams need synchronized joint states, multi-view camera data, wrist-level grasp detail, and rigorous QA before demonstrations become usable training episodes.

Lower cost per episode than US-based collection
100+
Usable episodes per station per day
2 wks
Pilot dataset delivery from task briefing
100%
Episodes reviewed before delivery
( 02 ) Services

Everything your
training pipeline needs.

🦾
Service 01
Teleoperation Data Collection

Human-operated bimanual robot demonstrations at scale. Leader-follower arm setup, synchronized multi-camera capture, 100% QA before delivery. ABC-compatible and LeRobot V2 native output.

Pick & Place Insertion Sorting Tool Use Assembly Folding
👁
Service 02
Egocentric Video Collection

First-person human motion data for embodied AI models. Household tasks, kitchen workflows, and object interaction captured from the human perspective using body sensors and multi-modal recording.

EgoVerse Compatible Body Sensors Multi-Modal Structured Labels
🏷
Service 03
Physical AI Annotation

Precision annotation for physical AI workloads. Every label human-verified. Gold labels, overlaps, and random sampling built into every batch — no synthetic shortcuts.

4D Point Cloud LiDAR 6DoF Pose RLHF SFT Scene Graphs
⚙️
Service 04
Seed + Iterate Policy Delivery

Beyond raw data — we deliver trained policies. Human demonstrations seed the model. Autonomous improvement loops run overnight. You receive working code at a target success rate, not just a dataset.

ACT Training DiT Compatible Policy Checkpoints W&B Logs
( 03 ) How It Works

From task briefing
to trained policy.

01
Task briefing

Tell us the task, environment, object types, and success criteria. We'll align on sensor configuration, camera angles, and output format — LeRobot V2, RLDS, HDF5, or your own spec.

02
Pilot batch delivery

We deliver a 50–100 episode pilot within 2 weeks. Review quality against your pipeline. No commitment required — the pilot is how we prove the data works before you scale.

03
Production collection

Approved pilot unlocks production throughput. 100+ usable episodes per station per day, rolling delivery, continuous QA. Scale up task coverage as your model needs evolve.

04
Policy delivery (optional)

Add our Seed + Iterate layer. Demonstration data bootstraps the policy. Autonomous improvement loops refine it overnight. You receive a policy at a target success rate with full training logs.

( 04 ) Why Dextri Data

Quality-first.
Built for your pipeline.

Format native

LeRobot V2. XDOF ABC. HDF5. RLDS. We speak your pipeline's language — no conversion overhead, no integration friction. Data loads in one line of Python.

QA at every layer

Every episode reviewed before delivery. Gold labels, random sampling, and overlap checks on every annotation batch. The same rigorous playbook as the best data operations in the world.

Task-specific, not generic

Open datasets are starting points. Your robot needs data for your specific tasks in your specific environments. We collect to your spec — not to what's convenient for us.

Cost structure that compounds

Our operational model delivers significantly lower cost per episode than US-based collection. More data per dollar means more training iterations, faster generalization, faster deployment.

ML-native team

Founded by ML engineers with ex-Meta and Amazon backgrounds. We understand your training stack, not just your data format. QA is done by people who can read a loss curve.

Scales to production

Start with a 50-episode pilot. Scale to thousands of episodes per week as your model matures. Our operational model expands with your data program without compromising quality.

( 05 ) Formats & Delivery

Every format
your stack needs.

Service Output Format Compatible With Pilot Turnaround
Teleoperation Episodes LeRobot V2 / HDF5 XDOF ABC, ACT, Diffusion Policy, Pi0 2 Weeks
Egocentric Video EgoVerse / MP4 + JSON Mecka EgoVerse, VLA models, GROOT 1 Week
Point Cloud Annotation LAS / PCD + labels LiDAR pipelines, 3D detection models Custom
RLHF Preference Data JSON / JSONL OpenAI, Anthropic, custom RLHF pipelines 1 Week
SFT Dataset JSONL / Parquet VLA fine-tuning, instruction following 1 Week
Seed + Iterate Policy Python + checkpoints PyTorch, LeRobot train.py, ABC DiT 4 Weeks
( 06 ) Start Here
Start with a free pilot batch.

No commitment. We deliver 50–100 episodes of your chosen task in 2 weeks. Evaluate quality against your pipeline before you sign anything. Available to qualified robotics labs and foundation model teams.

Request Pilot
info@dextridata.com
( 07 ) FAQ

Frequently
asked.

What does Dextri Data do?

We build physical AI training data infrastructure — teleoperation demonstration data, egocentric video collection, and precision annotation for robotics and embodied AI teams. We also deliver trained policies through our Seed + Iterate service.

Who is Dextri Data built for?

Robotics foundation model labs, humanoid hardware companies, and enterprise automation teams who need task-specific demonstration data, egocentric human motion data, or high-accuracy annotation for physical AI pipelines.

What formats do you support?

LeRobot V2, XDOF ABC / HDF5, RLDS, EgoVerse, JSON/JSONL, and custom formats. We align on output spec before collection starts — your data loads directly into your pipeline.

How does the pilot work?

Send us your task spec — task description, objects, success criteria, format requirements. We deliver a 50–100 episode batch within 2 weeks at no charge for qualified labs. If quality meets your bar, we scope a production contract from there.

What is Seed + Iterate?

Our premium policy delivery service. Human demonstration data seeds an initial behavior cloning policy. Autonomous improvement loops run overnight using the ENPIRE pattern. You receive a policy at a target success rate with full W&B training logs — not just raw data.

Do you build robots?

No. We are the data and annotation layer. We work alongside your hardware and model stack — not instead of it.