Verified professionals
Qualified experts, verified before they annotate.
Every contributor is credentialed and identity-verified, then matched to projects according to their medical specialty and expertise.
About Mango
Mango is the infrastructure for medical data annotation, putting verified clinicians on your labeling to build accurate, production-ready datasets.
Every annotation is completed by qualified experts and backed by a structured quality process and a permanent record of its origin.
From research institutions to enterprise AI teams, Mango brings clinical expertise into the data pipeline.
The premise
Trust starts with
who labels the data.
The quality of a medical AI model is determined long before deployment. Mango ensures every annotation is completed by verified medical professionals and backed by a transparent quality process.
Medical-grade quality
Clinical expertise, built into the workflow.
Structured review, validation checkpoints, and expert quality controls help ensure every label meets the requirements of the project.
Complete traceability
Every annotation has a verifiable origin.
Mango records who completed the work, when it happened, and how the annotation was reviewed through Mango Trail™.
• Mango trail •
Most annotation platforms deliver labels.
Mango delivers accountability.
Mango Trail™ is a permanent, verifiable record attached to every completed annotation.
Know exactly:
- Who completed the work
- Their verified medical specialty
- When it was completed
- How it was reviewed
- Its complete verification history
Every annotation, on the record
CHEST X-RAY · PANodule · 8mmMango Trail™ RecordSealed · Immutable
Verified AnnotatorRadiology specialist
RadiologistIdentity VerifiedCredentials VerifiedSpecialty Verified
Annotation LineageHover a node
• The process •
From expert to dataset.
A structured workflow designed to bring clinical expertise and accountability into every stage of annotation.
01Verify
Verify the expert.
Credentials, licensure, and identity are thoroughly confirmed before annotation work begins.
02Match
Match the expertise.
Specialists are aligned to datasets by specialty, expertise, and proven clinical experience.
03Annotate
Annotate, identity-bound.
Each session is tied to the verified clinician, so the work can’t be quietly handed off.
04Review
Review every submission.
Multi-stage validation and expert review help maintain consistent, medical-grade quality.
05Deliver
Deliver trusted data.
Production-ready datasets arrive with every annotation carrying its permanent Mango Trail™ record.
What we annotate
The clinical data we label.
Verified specialists, matched to the data type they're qualified to read.
Medical imaging
Radiology (X-ray, CT, MRI), read and labeled by clinicians who read scans for a living.
Pathology
Whole-slide images and histology, labeled by pathologists in the right subspecialty.
Clinical text and records
Extraction, coding, and structuring of clinical notes, reports, and EHR data.
Medical language models
Eval, safety review, and preference data for healthcare LLMs, graded against a clinician read.
Genomics and multi-omics
Variant interpretation and multi-omic data, labeled by qualified specialists.
Device and signal data
ECG, EEG and waveform data from medical devices and wearables, labeled by the clinicians who read them.
De-identification
PHI detection and redaction, so your data is safe before it's ever labeled.
Don't see yours?
If it takes a clinician to read it, we can put the right one on it.
Better healthcare AI
starts with better data.
Build expert-reviewed datasets with verified medical professionals, structured quality assurance, and complete annotation traceability.
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