As AI transforms teleoperation, remote patient monitoring, and robotic care, data annotation remains critical. From surgical robotics to ambient monitoring, healthcare and robotics AI teams require partners that can handle video, sensor, and time-series data labeling with precision and compliance. Below is a comparison of leading annotation service providers and platforms in this space.
This overview was developed by iMerit using publicly available information to help healthcare and robotics AI teams evaluate the right partners for building scalable, regulatory-grade datasets.
1. iMerit + Ango Hub
iMerit offers fully managed annotation services designed for medical and robotic AI. With trained clinicians and advanced tooling for multimodal data, iMerit delivers audit-ready datasets aligned with HIPAA and FDA requirements, supporting applications like fall detection, surgical guidance, and smart ICU monitoring through expert medical data labeling.
- US-board-certified clinicians and trained annotators
- HIPAA, FDA, and ISO-aligned QA workflows
- Multimodal data support: video, telemetry, audio, biosignals
- Ango Hub platform with model-in-the-loop and QC tools
- Foundation model dataset preparation and clinical validation
Why iMerit stands out:
The only provider on this list combining expert medical data annotation with platform-driven, regulatory-grade delivery for clinical and teleoperation AI.
2. Sama
Sama provides large-scale annotation across video and sensor data with strong ethical sourcing and security standards. It’s a reliable choice for robotics and healthcare-adjacent use cases, but may require domain experts for clinical-quality outcomes.
- Human-in-the-loop QA and scalable labeling workflows
- Supports video, robotics sensor, and medical data
- HIPAA and ISO 27001 compliant infrastructure
- Enterprise experience in healthcare, mobility, and robotics
Limitations:
- Does not provide clinical experts or validation
- Limited in healthcare-specific tooling integrations
Highlight: Sama is a capable partner for teams needing scale, speed, and secure infrastructure, especially for non-diagnostic use cases.
3. CloudFactory
CloudFactory enables teams to build custom remote annotation teams for video, audio, and sensor data across healthcare and robotics applications. While highly scalable, it places the burden of workflow design and clinical oversight on the client.
- Supports multimodal data, including video, vitals, and telemetry
- Dedicated team model for consistent quality and workflow ownership
- HIPAA and ISO 27001 capable
- Flexible integration with client tools or internal platforms
Limitations:
- No medical expert review is included by default
- Requires upfront training and onboarding effort
Highlight: A good option for long-term projects with consistent data pipelines, especially for companies that have internal domain knowledge.
4. Labelbox
Labelbox offers a self-serve platform for managing annotations across video, time-series, and sensor data. Ideal for teams that want flexibility and control, it supports automation, model feedback loops, and customizable QA pipelines.
- UI and SDK support for video, time-series, and telemetry
- Integrated QA tools and model-assisted labeling
- Optional Labelbox Boost workforce for managed tasks
- Cloud collaboration and automation-ready
Limitations:
- No built-in medical expertise or regulatory alignment
- Users must bring their annotation team (unless using Boost)
Highlight: A competent partner for AI-first teams that need annotation infrastructure but already have or plan to manage their labeling resources.
5. SuperAnnotate
SuperAnnotate combines a fast, user-friendly platform with support for complex data types like video, audio, and time-series. It offers optional workforce services, but clients handling healthcare data must bring clinical QA into their pipeline.
- All-in-one annotation suite with strong video and audio tools
- Optional managed annotation services
- Real-time feedback, version control, and model-in-the-loop
- Suitable for robotics and behavioral data annotation
Limitations:
- No regulatory alignment or healthcare-specific workflows
- Clinical oversight must be handled externally
Highlight: A valid option for tech teams working on robotic vision, sensor fusion, or behavioral recognition who need flexible tooling with optional workforce support.
6. Tasq.ai
Tasq.ai uses a micro-tasking and consensus model to label video and sensory events at scale. It’s suited to ambiguous data like human behavior in teleoperation feeds, but requires strong QA and is not yet common in regulated healthcare.
- AI-driven microtask distribution for ambiguous or high-volume labeling
- Works well for gesture recognition, fall risk analysis, and event detection
- API integration and modular workflow setup
- Built-in validation via worker consensus
Limitations:
- Not healthcare-specific or HIPAA aligned
- Not designed for small batch or high-expertise annotation
Highlight: A crowdsourced engine for difficult video classification tasks, useful for scaling fall risk or teleoperation feedback data when clinical validation is not required.
Comparison Table: Teleoperation & Patient Monitoring AI Annotation Providers
| Feature | iMerit + Ango Hub | Sama | CloudFactory | Labelbox | SuperAnnotate | Tasq.ai |
| Medical expert annotation | ✅ US clinicians | ❌ | ❌ | ❌ | ❌ | ❌ |
| HIPAA / FDA-aligned QA | ✅ | ✅ HIPAA infra | ✅ HIPAA capable | ❌ | ❌ | ❌ |
| Video annotation support | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
| Sensor / time-series data | ✅ Telemetry, vitals, biosignals | ✅ | ✅ | ✅ | ✅ | ✅ |
| Foundation model dataset prep | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Fully managed service | ✅ | ✅ | ✅ (client-trained teams) | Optional (Boost) | Optional | ❌ |
| Platform with model-in-the-loop | ✅ Ango Hub | Limited | Limited | ✅ | ✅ | ✅ |
| Scalable workforce | ✅ Dual-shore | ✅ | ✅ | ✅ | ✅ | ✅ Crowd |
| Clinical validation & oversight | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
| Regulatory-grade audit trails | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |
Why Choose iMerit for Healthcare Teleoperation and Patient Monitoring AI
iMerit offers clinical-grade annotation, expert-in-the-loop QA, and audit-ready datasets across robotic, surgical, and patient monitoring use cases. From sensor fusion to foundation model training, iMerit delivers scalable medical data labeling pipelines for teams deploying AI in safety-critical environments.
Learn more about our tele-operations solutions here.
Schedule a Demo or Contact Us to explore how iMerit can support your healthcare teleoperations initiatives.
