Expertly annotated by certified clinical professionals. Rigorously evaluated. Ethically sourced. — Powering the next generation of medical AI.
Everything you need to build, train, and validate clinical-grade AI — from a single, trusted partner.
"Source the right healthcare data — ethically, at scale."
We acquire, de-identify, and supply high-quality healthcare datasets through direct purchase, revenue-sharing partnerships, bespoke collection, and our curated Data Marketplace. Every dataset is consent-managed and traceable.
Key Points
"Turn raw clinical data into AI-ready training sets — with clinical precision."
Our certified healthcare professionals transform raw, unstructured medical data into structured, high-quality training datasets. Every project is delivered through a managed annotation lifecycle and a rigorous three-tier clinical QA process.
Key Points
"Validate your healthcare AI before it touches a patient."
Clinical AI errors cause real patient harm. Our expert evaluators assess AI model outputs against clinical ground truth, perform structured red-teaming, test for bias across patient populations, and build RLHF preference datasets for model alignment.
Key Points
Unlike generic crowd-sourced platforms, SCILabel connects you with a global network of specialized medical professionals. Our workforce is vetted for expertise in high-stake diagnostic domains.
Annotate, classify, and structure clinical text — from discharge summaries to patient notes — so healthcare AI can understand the language medicine is actually written in.
Our skilled Annotators and Evaluators
Label and segment medical images — X-rays, MRIs, pathology slides, and more — helping diagnostic AI systems learn to identify findings with clinical precision.
Our skilled Annotators and Evaluators
You'll review and rank AI-generated clinical responses, flagging errors and unsafe outputs so that healthcare AI learns from the best human judgment — yours.
Our skilled Annotators and Evaluators
Annotate genomic variants, biomarkers, and research datasets that train AI to power the next generation of personalized diagnostics and treatment.
Our skilled Annotators and Evaluators
Evaluate AI systems against global regulatory and ethical standards — auditing for bias, assessing risk, and ensuring that clinical AI is ready for the real world.
Our skilled Annotators and Evaluators
We collect, annotate, and evaluate the full spectrum of clinical and biomedical data types.
Not sure which data type you need? Talk to our team →
Whether you're sourcing data or earning from your clinical expertise — here's how it works.
Client Journey — 5 Steps
Tasker Journey — 5 Steps
Demonstrated output from a certified clinical workforce — the numbers behind how SCILabel delivers.
Across 5 specialist tracks
Covering every clinical modality
On every annotation project
Protecting every dataset
SCI-certified, de-identified clinical datasets — inspect the specs and license in days, not quarters.
SCILabel delivered annotated radiology data with a level of clinical precision we couldn't find anywhere else. The multi-tier QA process gives us complete confidence in the labels.
As a radiographer, I can now apply my clinical expertise to meaningful AI projects from home. The platform is intuitive, the guidelines are clear, and payments are always on time.
The revenue-sharing model means our de-identified imaging archive continues to generate value for our research budget. SCILabel's ethical sourcing standards match our own.
Bridging the gap between raw medical records and compliant AI development through secure data provenance, certified annotation, and borderless regulatory adherence.
De-identified to HIPAA Safe Harbor & Expert Determination standards.
Data Processing Agreements available for all EU clients.
Every annotator holds a verified healthcare qualification.
Compliant with the Kenya Data Protection Act 2019.
Nairobi-based, Pan-African expertise.
3-tier quality assurance on every project.
Everything you need to know about SCILabel, earning potential, and career support
Join leading medical institutions and AI startups using SCILabel to power the next generation of healthcare breakthroughs.
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