How it works
BRIDGEAboutBlogContact Us
Real-World Data for Physical AI

Real-World Data for Physical AI

Humyn Labs collects and annotates multi sensor datasets, camera, radar, and IMU, in real world environments where simulation falls short, so your physical AI models perform beyond the lab.

Problem Module

Physical AI models need massive volumes of real-world sensor data to operate safely outside simulation. But the sim-to-real gap is brutal: synthetic environments miss edge cases, rare scenarios, and the messy physics of the real world. Collecting synchronized multi-sensor data in the field is expensive, logistically complex, and requires domain expertise that most annotation vendors simply don't have.

Key Benefits

Structured. Defensible. Scalable.

Real-World Collection, Not Just Annotation

We don’t just label. At Humyn Labs, we deploy verified teams to capture data in real environments your model needs to understand.

Multi-Sensor Fusion Annotation

Our annotators work across multiple synced devices to deliver to single, coherent datasets.

Domain Experts Who Understand Autonomy

Every physical AI annotator has verified experience in autonomy, robotics, or spatial computing and not general crowd workers learning on the job.

Multi-Layer Quality Control

Every annotation passes peer review QC and centralized checks. For safety critical use like autonomous driving, we add a domain expert review layer.

How it Works (3-step process)

Structured. Defensible. Scalable.

Define Your Data Requirements

Tell us the sensor configuration, environment types, edge cases, and annotation schema your model needs. We design a collection and annotation plan around your pipeline.

We Collect and Annotate

Verified field teams capture multi-sensor data in the real world. Domain experts label it with 3D boxes, segmentation, tracking, and scene classification.

Deliver QC-Verified Datasets

Every dataset passes multi-layer QC before delivery. Get production-ready data in KITTI, nuScenes, or custom formats, with full provenance documentation.

Define Your Data Requirements 01
We Collect and Annotate02
Deliver QC-Verified Datasets03
WHAT WE COVER

Capabilities

Data Types We Collect and Annotate

Data Types

Data Types

  • Multi-camera video datasets (surround-view, stereo)
  • IMU / motion / odometry data
  • Robotic manipulation datasets (pick-and-place, grasping, assembly)
Annotation Types

Annotation Types

  • 3D bounding box annotations
  • Semantic segmentation for point clouds
  • Object tracking across frames
  • Scene classification and tagging
  • Sensor calibration validation
hero-background

USE CASES

Built for Teams
Building the Future of AI

(01)

Robotics
Companies

Manipulation datasets, navigation data, and human-robot interaction scenarios.

(02)

Industrial
Automation Teams

Factory floor data for inspection robots, pick-and-place systems, and autonomous forklifts.

Your model needs real-world data. Let's collect it.

Tell us about your sensor stack and use case. We'll scope a collection and annotation plan within 48 hours.

Got Questions? Check Our FAQ's

FAQ

Physical AI data is sensor data collected from the real world — including camera feeds, radar returns, and IMU readings — used to train AI models that operate in physical environments. This includes autonomous vehicles, robots, drones, and industrial automation systems.

Synthetic data is useful for initial training, but the sim-to-real gap means simulated environments miss edge cases, rare scenarios, and real-world physics variability. Production-grade physical AI models require real-world data to achieve the reliability and safety needed for deployment.

Humyn Labs supports multi-camera arrays (surround-view and stereo), radar, IMU/motion sensors, GPS/GNSS, and ultrasonic sensors. We handle multi-sensor synchronization and calibration as part of our collection process.

Every dataset goes through multi-layer quality control: peer review by fellow annotators, centralized QC by our quality team, and for safety-critical applications, an additional domain-expert review. We also provide full annotation provenance and inter-annotator agreement metrics.

We deliver in industry-standard formats including KITTI, nuScenes, Waymo Open Dataset format, COCO 3D, and custom schemas. All datasets include calibration files, timestamp synchronization metadata, and format conversion support.

Unlike most annotation vendors who only label existing data, Humyn Labs handles end-to-end real-world data collection and annotation. Our annotators are verified domain experts with on-chain reputation, and every dataset goes through double-verified quality control — peer review plus centralized QC.

Humyn Labs is a data collection company built for the AI era. We provide end-to-end data sourcing and AI data collection services across every non-text modality: voice, image, video, audio, and sensor data. Our platform connects AI companies directly with verified domain experts — eliminating the middleman overhead of traditional data collection agencies. Whether you need multilingual speech datasets, annotated medical images, or paired video-transcript data for multimodal models, Humyn Labs delivers custom datasets at scale with multi-layer quality control. We serve frontier AI labs, niche AI brands, robotics companies, and researchers who need production-grade training data that off-the-shelf datasets and crowd platforms cannot provide.