Centaur Labs Alternatives: Medical Labeling vs Physical AI Capture
Last updated: April 2, 2026. If anything here is inaccurate, email [email protected].
TL;DR
- Centaur Labs combines expert medical knowledge with an algorithmic quality system to label medical data.
- The company reports 177MM total labels completed, 2MM labels per week, and 20,000+ labeling subject matter experts.
- Centaur Labs supports multiple health data types including text, audio, waveform (EEG/ECG), 2D images, 3D images, and video.
- The platform emphasizes expert-quality annotation with Gold Standard cases and pay-for-performance incentives.
- Centaur highlights HIPAA and SOC 2 Type II compliance for healthcare data labeling.
- MIT News describes Centaur's DiagnosUs app for gathering expert medical opinions at scale.
- Claru is purpose-built for physical AI capture and enrichment.
- Choose Centaur Labs for medical expert labeling; choose Claru for capture + enrichment of robotics data.
What Centaur Labs Is Built For
Key differences in 60 seconds: Centaur Labs focuses on expert medical labeling and health data workflows. Claru is a capture-and-enrichment pipeline for physical AI training data.
Centaur Labs highlights expert medical labeling with algorithmic quality systems to combine expert opinions at scale.[1]
The company reports 177MM total labels completed, 2MM labels per week, and 20,000+ labeling subject matter experts.[2]
Centaur Labs supports multimodal health data types including text, audio, waveform (EEG/ECG), 2D images, 3D images, and video.[3]
The health data labeling solution emphasizes Gold Standard cases and pay-for-performance incentives to measure annotator accuracy.[4]
Centaur Labs notes HIPAA and SOC 2 Type II compliance and healthcare labeling tools like digital pathology and DICOM viewers.[5]
MIT News describes Centaur's DiagnosUs mobile app for collecting expert medical opinions on biomedical data at scale.[6]
If your bottleneck is expert medical labeling and healthcare workflows, Centaur Labs is a strong fit. If your bottleneck is physical-world capture and enrichment for robotics, Claru is the better fit.
Company Snapshot
- Focus
- Expert medical data labeling with algorithmic quality systems.[1]
- Scale
- 177MM total labels, 2MM labels per week, 20,000+ SMEs.[2]
- Modalities
- Text, audio, waveform, 2D/3D images, video.[3]
- Quality controls
- Gold Standard cases and pay-for-performance incentives.[4]
- Compliance
- HIPAA and SOC 2 Type II for healthcare data workflows.[5]
- Best fit
- Healthcare and high-stakes medical AI labeling
- Focus
- Physical AI training data for robotics and world models
- Capture
- Wearable camera network plus task-specific collection
- Enrichment
- Depth, pose, segmentation, optical flow, aligned captions
- Best fit
- Robotics teams that need capture + enrichment
Key Claims (With Sources)
- Centaur Labs combines expert medical labeling with algorithmic quality systems and on-demand expert networks.[1]
- The company reports 177MM total labels completed, 2MM labels per week, and 20,000+ labeling subject matter experts.[2]
- Centaur Labs supports multimodal data types including text, audio, waveform (EEG/ECG), 2D/3D images, and video.[3]
- Health data labeling includes Gold Standard cases, pay-for-performance incentives, and HIPAA/SOC 2 Type II compliance.[4][5]
- MIT News describes Centaur's DiagnosUs app for gathering expert medical opinions on biomedical data.[6]
Where Centaur Labs Is Strong
Expert medical labeling
Centaur Labs uses expert networks and algorithmic quality controls for medical data labeling.[1]
Healthcare compliance
The health data labeling solution emphasizes HIPAA and SOC 2 Type II compliance and specialized medical viewers.[5]
Scale of expert opinions
Centaur Labs reports 2MM labels per week with 20,000+ SMEs.[2]
Why Physical AI Teams Evaluate Alternatives
Capture-first pipelines
Physical AI models require real-world data collection with task-specific capture programs.
Enrichment layers
Depth, pose, segmentation, and motion signals are critical for robotics training.
Training-ready delivery
Claru ships datasets in formats that plug directly into robotics stacks.
Centaur Labs vs Claru: Side-by-Side Comparison
| Dimension | Centaur Labs | Claru |
|---|---|---|
| Primary focus | Expert medical data labeling and quality systems.[1] | Physical AI training data for robotics and world models |
| Scale | 177MM labels completed, 2MM per week, 20,000+ SMEs.[2] | Specialized capture network focused on physical tasks |
| Modalities | Text, audio, waveform, 2D/3D images, video.[3] | Egocentric video, manipulation, depth, pose, segmentation |
| Compliance | HIPAA and SOC 2 Type II compliant healthcare workflows.[5] | Secure capture workflows and training-ready delivery |
| Best fit | Healthcare and high-stakes medical AI labeling | Robotics teams needing capture + enrichment |
Deep Dive: Centaur Labs vs Claru
Centaur Labs focuses on expert medical labeling. Claru focuses on capture and enrichment for physical AI.
Expert labeling vs capture pipelines
Centaur Labs emphasizes expert medical labeling with quality systems.
Claru emphasizes real-world capture and enrichment for robotics training.
Healthcare data vs physical-world data
Centaur Labs is optimized for clinical and biomedical data types.
Claru is optimized for physical-world tasks and robotic manipulation.
Where each provider fits
Centaur Labs is a strong fit for healthcare labeling needs.
Claru is a better fit when you need robotics-ready datasets.
When Centaur Labs Is a Fit
- You need expert labeling for medical imaging or clinical data.
- You require HIPAA- and SOC 2-aligned healthcare workflows.
- You need multimodal medical data labeled at scale.
When Claru Is a Fit
- You need new physical-world data captured for robotics tasks.
- Your model depends on enrichment layers like depth and motion.
- You want datasets delivered in robotics-native formats.
How Claru Delivers Physical AI Data
Claru provides an end-to-end pipeline so physical AI teams can move from brief to training-ready data quickly.
Scope the Dataset
Define the target behaviors, environments, and label schema with your research team. We align on formats, enrichment layers, and success criteria before capture begins.
Capture Real-World Data
Activate the collector network, teleoperation runs, or game-based capture to gather the exact clips your model needs.
Enrich Every Clip
Generate depth maps, pose, segmentation, and optical flow in batch. Cross-validate signals to ensure aligned training inputs.
Expert Annotation
Specialized annotators label action boundaries, affordances, and intent using project-specific guidelines and QA checks.
Deliver Training-Ready
Ship datasets in WebDataset, HDF5, RLDS, or your native format with manifests, checksums, and datasheets.
Claru by the Numbers
Other Alternatives Worth Considering
If you are mapping the data provider landscape, these comparisons cover adjacent options.
How to Choose
If you need expert medical labeling with healthcare compliance, Centaur Labs is designed for that scope.
If you need capture and enrichment of physical-world data for robotics training, Claru is a better fit.
Some teams use both: Centaur Labs for medical labeling, Claru for physical datasets.
Frequently Asked Questions
What is Centaur Labs?
Centaur Labs provides expert medical data labeling with algorithmic quality systems.[1]
What data types does Centaur Labs support?
Centaur Labs lists text, audio, waveform, 2D/3D images, and video data types for medical labeling.[3]
How does Centaur Labs scale expert labeling?
The company reports 2MM labels per week and 20,000+ SMEs to scale expert annotation.[2]
When is Claru a better fit?
Claru is a better fit when you need capture, enrichment, and delivery of robotics-ready datasets.
Need Physical AI Data That Ships Fast?
Tell us what you are training. We will scope a capture plan and deliver a pilot dataset in days.