Who We Are

About Us

ego data collection

Who We Are

Embodied AI Data, Built for Real-World Learning

MovraWorks is an embodied AI data company. We design and operate real-world data collection programs for robot learning, vision-language-action models, and Physical AI.

Our work covers egocentric, UMI, teleoperation, human demonstration, and custom multimodal data. We help teams move from a small pilot to a repeatable production workflow with clear specifications, trained operators, quality checks, and documented delivery.

What We Do

We build task-specific datasets for embodied intelligence. A typical program may combine synchronized video, robot or device state, pose, control signals, audio, sensor telemetry, task events, and structured annotations.

Every engagement starts with the target model and use case. We define tasks, environments, hardware, schemas, acceptance criteria, and privacy requirements before collection begins, then validate them in a pilot before scaling.

We value accurate specifications, traceable quality decisions, secure data handling, and straightforward communication. When a requirement or trade-off is unclear, we surface it early instead of hiding it in the final delivery.

Egocentric Data Collection

First-person visual and sensor data captured in real homes, workplaces, and task environments.

UMI & Teleoperation Data

Time-aligned observations, actions, device states, and outcomes for robot policy learning.

Human & Multimodal Data

Expert demonstrations and custom sensor combinations organized into training-ready datasets.

Built for robotics, VLA, and Physical AI teams

Let’s Work Together

Why Teams Work With MovraWorks

Good embodied AI data is not created by volume alone. It comes from clear task design, stable capture systems, consistent execution, and quality criteria that can be checked. We build those controls into the program from the beginning.

We translate model goals into executable tasks, sensor requirements, operator instructions, sampling plans, and acceptance criteria before production starts.

Automated validation and trained reviewers check synchronization, completeness, visibility, task execution, annotations, and other project-specific requirements.

We work with standard and custom devices across video, depth, motion, robot state, force, tactile, audio, and metadata, and deliver data in the schema your pipeline requires.

Projects use controlled access, documented handling procedures, issue tracking, and agreed delivery checks. You can see what passed, what failed, and why.

Our Commitment to You

We treat dataset requirements as engineering requirements. Scope, quality thresholds, exceptions, and delivery formats are documented before production. Progress is reviewed against those decisions, so the final dataset is understandable, auditable, and useful to your team.

01

Pilot Before Scale

Validate tasks, sensors, schema, throughput, and acceptance criteria before production.
02

Quality at Every Stage

Monitor collection, review representative samples, and resolve issues before final delivery.