KeenTruth · Embodied AI Data Engineering

Embodied AI data annotation and governance, built for training-ready delivery.

KeenTruth works with embodied AI model developers, robotics OEMs, and AI data providers. Powered by our proprietary data platform, we take customer-supplied data from ingestion and governance through expert annotation and quality validation.

We deliver validated data that can move directly into model-training workflows.

Nearly 10 Years of Experience · Full-Spectrum Embodied Data Governance · VLM-Assisted Annotation & QA · End-to-End Data Delivery

Real-robot task data with ROS 2 topic quality analysis
UMI data with gripper state and trajectory quality analysis
Egocentric hand keypoints and action segment annotation
Nearly 10 YearsAutonomous-driving + embodied AI algorithms and data operations
1M+ HoursHistorical data volume handled by the team
98%First-pass acceptance rate
Industry-benchmark data production efficiency

Why specialized engineering

Annotation alone does not make embodied data training-ready.

Embodied AI data combines visual observations, robot states, actions, controls, sensor streams, and task semantics. Missing records, topic anomalies, timing drift, unclear boundaries, or conflicting labels can reduce the value of an entire batch.

01

Heterogeneous data is difficult to normalize

Different devices, software versions, collection pipelines, and task environments rarely produce one consistent structure.

02

Annotation standards are difficult to scale

Model requirements must become instructions that annotators and reviewers can execute consistently.

03

Quality issues spread quickly

Quality controls must begin during pilot annotation and continue through production, review, correction, and acceptance.

End-to-end workflow

From customer-supplied raw data to training-ready delivery

  1. 01Data Ingestion & Profiling
  2. 02Data Governance
  3. 03Specification & Pilot
  4. 04Expert Annotation
  5. 05Quality Validation
  6. 06Standardized Delivery

Three data environments

Specialized workflows for high-value embodied AI data

Purpose-built workflows aligned to one standard for quality, semantics, and traceability.

01

Real-Robot Data

A real robot performing a tabletop manipulation task

Teleoperation, leader–follower arms, demonstrations, and autonomous execution.

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02

UMI Data

UMI wrist camera, gripper, and fisheye observation view

Device view, trajectories, gripper state, tactile signals, and task process.

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03

Egocentric Data

A collection of egocentric first-person task views

First-person tasks, actions, objects, hands, and interaction relationships.

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Proprietary data platform

Platform, models, and operations working as one delivery system

KeenTruth’s proprietary platform connects data ingestion, task configuration, annotation, review, quality tracking, and output—with VLM-assisted annotation and QA, workforce management, multi-format processing, and end-to-end traceability.

VLM-Assisted AnnotationVLM-Assisted QAWorkforce ManagementProgress TrackingMulti-Format ProcessingEnd-to-End Traceability

Quality & Security

Verifiable quality. Protected customer data.

Customer data is used only for the agreed project. It is not disclosed to unauthorized third parties, reused for other customers, or used for unrelated purposes.

Typical Solutions

Supporting the teams building the embodied AI stack

01

Embodied AI Model Developers

Create consistent task semantics and action hierarchies for reliable VLA training.

02

Robotics OEMs

Govern complex, multi-source real-robot data and reduce repetitive preprocessing.

03

Embodied AI Data Providers

Combine VLM assistance, human expertise, and operations for scalable, traceable delivery.

Contact

Move raw embodied data into training faster.

Tell us about your data, annotation requirements, and quality expectations.