Our process

Project scoping

We begin with a detailed consultation to understand your medical AI project requirements. Our team works with you to define:

• • Project scope, timeline, and deliverables
• • Required medical specialties and expertise levels
• • Data annotation guidelines and quality standards
• • Compliance requirements (HIPAA, GDPR, etc.)
• • Budget and resource allocation

Expert matching

From our network of 12,000+ board-certified physicians, we carefully select experts who match your specific needs:

• • Specialty-specific clinical experience
• • Relevant subspecialty training
• • Track record of high-quality annotations
• • Availability and capacity to meet deadlines
• • Previous AI/ML project experience (if required)

Training & calibration

Before production work begins, we conduct comprehensive training to ensure consistency:

• • Detailed review of annotation guidelines
• • Platform and tool training
• • Practice annotation rounds with feedback
• • Inter-annotator agreement testing
• • Quality threshold validation

Production annotation

Experts begin annotating your medical data with ongoing quality monitoring:

• • Systematic data processing workflows
• • Real-time quality metrics tracking
• • Regular consensus meetings for edge cases
• • Continuous feedback and guideline refinement
• • Progress reporting and milestone tracking

Quality assurance

Multi-layer QA process ensures the highest annotation quality:

• • Random sample review by senior experts
• • Statistical quality control checks
• • Inter-annotator agreement analysis
• • Edge case escalation and resolution
• • Final validation before delivery

Delivery & iteration

Final annotated data is delivered with full documentation and support:

• • Secure data transfer to your systems
• • Comprehensive quality metrics report
• • Annotation methodology documentation
• • Post-delivery support for any issues
• • Capability for iterative refinement