datraAI

Turning physical work into training-ready trajectories

DatraAI is the multimodal data layer for embodied AI. We capture, synchronize, and structure real-world interactions into high-fidelity trajectories that power training and accelerate deployment.

See Actuate
Technician carrying an industrial tote toward a robot arm in a data-capture lab
Data layer for embodied AI01 / 04
datraai.com

ACTUATE / MULTIMODAL DATA INFRASTRUCTURE

From raw motion to model-ready trajectories.

Synchronize human and robot data, recover task structure, and export trajectories directly into the training stack you already use.

Explore Actuate ↘
ACTUATE / LIVE COMPOSITION04 STREAMS
CAPTURESYNCEXPORT
INPUT / EGO · DEPTH · UMI · TELEOPPROCESS / SYNC · QC · PERCEPTION · RETARGETOUTPUT / LEROBOT · RLDS · HDF5

Backed by

Founders, Inc.
The Residency
NVIDIAInception program

THE PROBLEM

Physical work is continuous. Training data usually isn’t.

Every capture system has its own clocks, coordinate frames, sampling rates, and schema. Actuate resolves that fragmentation before training begins.

04
Input families
08
Processing stages
04+
Export schemas

Built between capture and training.

The infrastructure that turns continuous demonstrations into usable robot behavior.

01 / PROCESS

Actuate

A hardware-agnostic pipeline that aligns clocks, recovers task structure, extracts perception signals, and exports model-ready behavior.

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02 / CAPTURE

Field capture

Continuous human demonstrations captured through owned egocentric wearables and adaptable stereo, depth, UMI-style, and teleoperation rigs.

ACTUATE

Different sensors.
One trajectory.

Every rig produces different timestamps, coordinate frames, sample rates, and schemas. Actuate resolves that fragmentation before training begins.

01Ingestion
02Temporal sync
03Quality control
04Segmentation
05Perception
06Trajectory construction
07Retargeting
08Export
OUTPUT

observationt→statet→actiont→observationt+1

Supported now

We are deliberately focused on four data families rather than every possible robotics sensor.

EGO

Egocentric

First-person RGB and IMU from continuous human task demonstrations.

3D

Stereo / depth

Calibrated camera and depth streams for geometry and spatial understanding.

UMI

UMI-style

Portable manipulation capture with camera, gripper, and end-effector trajectories.

TEL

Teleoperation

Robot observations, state, and actions captured during human-controlled execution.

Primary capture today: first-person RGB, accelerometer, and gyroscope from continuous human demonstrations using Panoculon Labs wearable devices.

Data in motion

Public research demonstrations representative of the input families Actuate is built to process. Videos remain attributed to their original teams.

CAREERS / DATRAAI

Make physical intelligence possible.

Build the systems that teach robots from real work.

See open roles ↗