Verify medical professionals.
Credentials, licensure, and identity confirmed before any annotation work begins.
About Mango
Mango is the infrastructure for medical data annotation, putting verified medical professionals on your labeling and delivering it with a complete record of who did the work.
Every annotation is completed by qualified experts, reviewed through structured quality workflows, and backed by Mango Trail, providing complete transparency from contributor verification to final delivery.
From research institutions to enterprise AI teams, Mango delivers the verified labels behind the next generation of healthcare AI.
The premise
The quality of an AI model is determined long before deployment. It starts with the people who label the data.
Mango ensures every annotation is completed by verified medical professionals and backed by a transparent quality process.
01
Every contributor is credentialed, identity verified, and matched to projects based on their medical specialty and expertise.
02
Built-in review workflows, validation checkpoints, and quality controls ensure every label meets enterprise standards.
03
Every annotation carries a permanent record of who completed it, when it was completed, and how it was reviewed.
The platform
From onboarding qualified specialists to delivering production-ready datasets, Mango provides the infrastructure healthcare AI teams need to scale with confidence.

The process
01/05
Credentials, licensure, and identity confirmed before any annotation work begins.
Specialists are aligned to datasets by specialty, expertise, and proven clinical experience.
Purpose-built tools designed around clinical workflows, precision, and diagnostic accuracy.
Multi-stage validation and expert consensus keep quality consistently medical-grade.
Get production-ready datasets, with every annotation carrying its permanent Mango Trail record.
Most annotation platforms deliver labels. Mango delivers accountability. Mango Trail is a permanent, verifiable record attached to every completed annotation.
Know exactly:
Built for teams
Every annotation passes through structured quality assurance.
Experts are matched to projects based on medical specialty.
Know who created every data point and how it was reviewed.
Enterprise-grade identity verification protects every project.
Data types
Verified specialists, matched to the data type they're qualified to read.
Radiology (X-ray, CT, MRI), read and labeled by clinicians who read scans for a living.
Whole-slide images and histology, labeled by pathologists in the right subspecialty.
Extraction, coding, and structuring of clinical notes, reports, and EHR data.
Evaluation, safety review, and preference data for healthcare LLMs, graded against a clinician read.
Variant interpretation and multi-omic data, labeled by qualified specialists.
PHI detection and redaction, so your data is safe before it's ever labeled.
Train production-ready clinical models on verified, expertly labeled medical data.
Get training data whose provenance holds up to FDA scrutiny, every label tied to a verified specialist.
Scale annotation without trading away quality, accuracy, or the proof of who did the work.
High-quality labels from qualified medical experts, with a record you can publish and defend.
Verified clinical annotation, done for you, as you build your own clinical AI.
Expertly annotated data for drug discovery and clinical research.