Surgical data collection captures procedure-grade demonstrations from clinician operators on research-grade surgical robots. Every trajectory is logged with sub-millimeter tool-tip pose, grip force, and stereo video — under HIPAA-compliant protocols with IRB approval and full de-identification.
Why outsource surgical data?
Clinician time is the bottleneck. We coordinate operators, handle IRB compliance, and deliver de-identified datasets so your ML team focuses on models, not protocols.
3 surgical platforms.
6 procedure types.
HIPAA compliant end-to-end.
Where we collect
41+ delivery centers across 12 countries. Every program runs from a Roborax hub near your target time zone.
Asia Pacific
India · Philippines
Americas
USA · Canada · Colombia · Jamaica · El Salvador · Belize
EMEA
UK · Albania · Kosovo · Morocco
Four streams produced by clinician operators, audited at sub-frame precision.
Surgeon-quality trajectories with tool-tip pose, sub-millimeter accuracy.
Force-torque profiles for contact-sensitive tasks where tissue trauma matters.
Operators with surgical training, not generic teleoperators. Bar matches OR standards.
Same procedure across body habitus, anatomy variation, and complication patterns.
A four-stage pipeline designed for IRB-compliant capture and FDA-grade audit trails.
Define the procedure, the success criteria, and the variation matrix with your clinical team.
Operators with surgical training matched to procedure type. Credentials verified.
Sub-millisecond synchronized capture in a HIPAA-bound environment. Audit trail per session.
Per-procedure quality review by a senior clinician. Failure cases flagged, not silently shipped.
Production and research surgical robots from across the field.
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Four verticals. One data partner.
Whole-body trajectories across 24 platforms.
Long-horizon tasks in real environments.
Pick-pack-place across real SKU diversity.
Remote operator-driven data collection.
In-person task demos for imitation learning.
Held-out test sets and success-rate scoring.
FAQ
Operators working in or around clinical environments are trained in infection control, patient privacy, and relevant local health regulations. Our program leads carry applicable certifications for the jurisdiction.
We do not collect patient data. Our programs capture robot motion and sensor data in clinical environments — not patient records, clinical observations, or any individually identifiable health information.
HIPAA in the US, GDPR in Europe, and equivalent frameworks in other jurisdictions. Our data handling practices are designed to comply with the most stringent applicable framework by default.
Any incidental capture of clinical staff, patients, or identifiable clinical information is reviewed and redacted before delivery. We can provide a documented anonymisation protocol on request.
Yes, with appropriate access coordination, credentialing, and infection control compliance. We have experience working within active hospital departments and surgical simulation centers.
From the blog
Training Data for Surgical Robots: HIPAA, Precision, and ScaleCompliance requirements and data standards for surgical robot training.
From the blog
The QA Pipeline Every Robotics Data Team NeedsQA standards for procedure-grade teleoperation data.
Tell us the platform and the procedure. We come back with a clinician roster and IRB plan.
FROM THE FIELD
A policy trained only on successful demonstrations has never seen what going wrong looks like. The first time a grasp slips, an object lands in
Most robots look great in the demo. The trouble starts in the field, where a reflective surface, an unusual object or a half-second sensor dropout
Research teams rarely lack ideas. They lack hours. Every month spent building rigs, calibrating cameras and recruiting operators is a month not spent on the
Hiring a data vendor feels like a procurement decision until the first batch arrives. Then it becomes a modelling problem. The operators your partner employs,
Collecting a real demonstration costs operator hours, hardware time and a scene. Synthetic data augmentation robotics teams now use can multiply what one demonstration is
Every robotics team eventually asks the same question: how much simulation is too much? The honest answer is that there is no universal real and
