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Objectways Alternatives: HITL Labeling vs Physical AI Data

Objectways provides human-in-the-loop data services across annotation, data collection, content moderation, and generative AI. If you need capture and enrichment for robotics, Claru is built for physical AI from day one. This page compares the two.

Last updated: April 2, 2026. If anything here is inaccurate, email [email protected].

TL;DR

  • Objectways lists data annotation, data collection, content moderation, and generative AI services.
  • It highlights human-in-the-loop labeling across text, image, audio, video, and LiDAR.
  • Objectways reports 500M+ labels delivered, 100+ customers, and 2,200+ trained annotators.
  • The company cites 6+ years of experience and eight global locations.
  • Objectways lists annotation tooling for video, PDF, NLP, OCR, pose, and audio tasks.
  • Security and compliance claims include SOC, ISO 27001, GDPR, and HIPAA.
  • Claru is purpose-built for physical AI capture and enrichment.
  • Choose Objectways for large-scale HITL labeling. Choose Claru for capture + enrichment of robotics data.

What Objectways Is Built For

Key differences in 60 seconds: Objectways is a human-in-the-loop data services provider across annotation, collection, and moderation. Claru is a physical AI pipeline focused on capture and enrichment for robotics.

Objectways lists AI data services including data annotation, data collection, content moderation, and generative AI. [1]

The company highlights human-in-the-loop labeling across text, image, audio, video, and LiDAR modalities.[2]

Objectways reports scale metrics including 500M+ labels delivered, 100+ customers, 2,200+ trained annotators, 6+ years of experience, and eight global locations. [3]

The site lists annotation tooling for video, PDF, NLP, OCR, hierarchical detection, pose estimation, and audio tasks.[4]

Objectways highlights security and compliance claims including SOC, ISO 27001, GDPR, and HIPAA.[5]

Objectways was founded in 2018 and has grown into a mid-market data services provider with operations across eight global locations. The company has built its reputation on high-volume annotation delivery, citing over 500 million labels completed. Its service model combines trained annotators with project management workflows, targeting enterprises that need consistent labeling throughput across multiple data types and compliance frameworks.

For physical AI and robotics teams, the key consideration is whether annotation services alone address the full data pipeline requirement. Embodied AI models typically need task-specific data captured in real-world environments with dense enrichment layers like depth estimation, pose tracking, instance segmentation, and optical flow. These signals serve as direct training inputs and must be temporally aligned with the source video. Annotation-only providers can label existing data but may not offer the capture infrastructure and enrichment processing that robotics training demands.

If your bottleneck is large-scale labeling and data operations, Objectways is a strong fit. If your bottleneck is physical-world capture and robotics enrichment, you need a capture-first pipeline.

Company Snapshot

Objectways at a Glance
Services
Data annotation, data collection, content moderation, generative AI. [1]
Scale
500M+ labels delivered and 100+ customers.[3]
Workforce
2,200+ trained annotators across eight global locations.[3]
Modalities
Text, image, audio, video, and LiDAR.[2]
Compliance
SOC, ISO 27001, GDPR, HIPAA.[5]
Best fit
Teams needing large-scale HITL labeling and data services
Claru at a Glance
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)

  • Objectways lists services for data annotation, data collection, content moderation, and generative AI. [1]
  • The company highlights human-in-the-loop labeling across text, image, audio, video, and LiDAR. [2]
  • Objectways reports 500M+ labels delivered and 100+ customers.[3]
  • Objectways cites 2,200+ trained annotators, 6+ years of experience, and eight global locations. [3]
  • Annotation tooling includes video, PDF, NLP, OCR, hierarchical detection, pose estimation, and audio tasks.[4]
  • Security and compliance claims include SOC, ISO 27001, GDPR, and HIPAA.[5]
  • Objectways states it was founded in 2018 and holds SOC 2 Type 2 and ISO 27001 certifications. [6]

Where Objectways Is Strong

Objectways emphasizes scale, multi-service coverage, and compliance-oriented delivery.

Large-scale labeling capacity

Objectways reports 500M+ labels delivered with 2,200+ trained annotators across eight locations.[3]

Service breadth

The company lists data annotation, data collection, content moderation, and generative AI services.[1]

Compliance posture

Objectways highlights SOC, ISO 27001, GDPR, and HIPAA compliance claims for enterprise programs.[5]

Why Physical AI Teams Evaluate Alternatives

Robotics teams often need capture and enrichment of physical-world data, not just labeling services.

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.

Objectways vs Claru: Side-by-Side Comparison

This comparison focuses on large-scale labeling services versus capture-first physical AI datasets.
DimensionObjectwaysClaru
Primary focusHuman-in-the-loop data services across annotation, collection, and moderation. [1]Physical AI training data for robotics and world models
Scale500M+ labels delivered and 2,200+ annotators.[3]Specialized capture network focused on physical tasks
ModalitiesText, image, audio, video, and LiDAR.[2]Egocentric video, manipulation, depth, pose, segmentation
ComplianceSOC, ISO 27001, GDPR, HIPAA.[5]Secure capture workflows and training-ready delivery
Best fitTeams needing HITL labeling at scaleRobotics teams needing capture + enrichment

Deep Dive: Objectways vs Claru

Objectways emphasizes scale and service breadth. Claru emphasizes capture and enrichment for physical AI.

Scale and workforce

Objectways reports 500M+ labels delivered with 2,200+ trained annotators.

Claru focuses on a specialized capture network tailored for robotics tasks.

Service breadth

Objectways covers data annotation, data collection, content moderation, and generative AI services.

Claru focuses on physical AI capture, enrichment, and robotics-ready delivery.

Robotics data requirements

Training embodied AI systems requires more than labeled datasets. Physical AI models depend on dense enrichment layers including monocular depth, human pose estimation, instance segmentation, and optical flow. These signals serve as direct model inputs and must be generated alongside capture to ensure temporal alignment and format consistency.

Objectways focuses on annotation and labeling services. Claru builds enrichment into the capture pipeline so depth, pose, and motion signals are generated as first-class outputs delivered alongside the source video in robotics-native formats.

Where capture matters most

If you already have data and need labeling at scale with compliance support, Objectways is a strong fit. The company's trained annotator workforce and multi-service coverage make it well suited for high-volume labeling programs across text, image, audio, video, and LiDAR modalities.

If you need new physical-world data with enrichment layers and robotics-native delivery, Claru is a better fit. The capture-first approach means data collection, enrichment, and formatting are handled end-to-end rather than requiring separate vendors for each step.

When Objectways Is a Fit

  • You need HITL labeling across multiple modalities.
  • You already have data and need annotation support at scale.
  • You want a provider with compliance and multi-service coverage.

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.

01

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.

02

Capture Real-World Data

Activate the collector network, teleoperation runs, or game-based capture to gather the exact clips your model needs.

03

Enrich Every Clip

Generate depth maps, pose, segmentation, and optical flow in batch. Cross-validate signals to ensure aligned training inputs.

04

Expert Annotation

Specialized annotators label action boundaries, affordances, and intent using project-specific guidelines and QA checks.

05

Deliver Training-Ready

Ship datasets in WebDataset, HDF5, RLDS, or your native format with manifests, checksums, and datasheets.

Claru by the Numbers

4M+
Human annotations
across egocentric video, game environments, manipulation data, and custom captures
500K+
Egocentric clips
captured from kitchens, warehouses, workshops, and outdoor environments worldwide
10,000+
Global contributors
trained collectors with wearable cameras across 100+ cities
Days
Brief to delivery
pilot datasets scoped and delivered in under a week

How to Choose

If you need HITL labeling across modalities with large-scale capacity, Objectways is designed for that scope.

If you need capture and enrichment of physical-world data for robotics training, Claru is the better fit.

Some teams use both: Objectways for labeling and Claru for physical datasets.

Frequently Asked Questions

What services does Objectways provide?

Objectways provides a suite of AI data services including data annotation, data collection, content moderation, and generative AI services. Founded in 2018, the company operates across eight global locations and serves over 100 customers. The service model combines trained human annotators with project management workflows to deliver labeled datasets across text, image, audio, video, and LiDAR modalities.[1]

What scale does Objectways report?

Objectways reports 500M+ labels delivered with 100+ customers and 2,200+ trained annotators across eight global locations. The company cites 6+ years of experience in AI data services. This scale makes Objectways a viable option for enterprise teams that need high-volume annotation throughput with consistent quality across multiple concurrent projects and data modalities.[3]

Does Objectways support LiDAR annotation?

Yes. Objectways lists LiDAR alongside text, image, audio, and video labeling as part of its multi-modal annotation services. LiDAR annotation is relevant for autonomous driving and 3D perception tasks. For robotics teams that also need enrichment layers like depth estimation and optical flow aligned to video capture, a provider with an integrated capture-and-enrichment pipeline may better serve the full data requirement.[2]

What compliance claims does Objectways list?

Objectways highlights security and compliance claims including SOC, ISO 27001, GDPR, and HIPAA certifications. These compliance postures are important for enterprise teams working with sensitive data, particularly in healthcare, financial services, and regulated industries. Teams evaluating Objectways should verify the specific certification scope and audit dates relevant to their project requirements.[5]

Is Objectways a fit for robotics data capture?

Objectways focuses on annotation and labeling services rather than capture-first physical AI data. While the company can annotate video and LiDAR data, it does not position itself as a capture pipeline for robotics training. Teams building embodied AI systems that require task-specific video capture in real-world environments, enrichment layers like depth and pose, and delivery in robotics-native formats should evaluate providers specifically designed for physical AI data pipelines.

When is Claru a better fit?

Claru is a better fit when your primary need is capturing new physical-world data and enriching it for robotics training. This includes scenarios where you need egocentric video from specific environments, enrichment layers such as monocular depth, human pose estimation, segmentation, and optical flow, and delivery in formats like WebDataset, HDF5, or RLDS. If you already have data and need annotation at scale with compliance support, Objectways may be the more appropriate starting point.

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