The verified clinician layer for medical AI.

Your model is only as good as the people who labeled its data, and most teams can't prove who that was. Mango puts licensed, verified clinicians behind every label and keeps proof of who did the work.

Licensed clinicians · Specialty-matched · Provable provenance · Session-bound · De-identified

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.

VerifiedAnnotatedCertifiedmango.traillicense - specialty - sessionsigned record

The premise

Every model begins with
trustworthy data.

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

Verified professionals

Every contributor is credentialed, identity verified, and matched to projects based on their medical specialty and expertise.

02

Medical-grade quality

Built-in review workflows, validation checkpoints, and quality controls ensure every label meets enterprise standards.

03

Complete traceability

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.

Designed for every stage of medical data annotation.

Clinician reviewing laboratory result sheets

The process

From expert to labeled data.

01/05

01VERIFY

Verify medical professionals.

Credentials, licensure, and identity confirmed before any annotation work begins.

02MATCH

Match experts to projects.

Specialists are aligned to datasets by specialty, expertise, and proven clinical experience.

03ANNOTATE

Annotate with precision.

Purpose-built tools designed around clinical workflows, precision, and diagnostic accuracy.

04REVIEW

Review every submission.

Multi-stage validation and expert consensus keep quality consistently medical-grade.

05DELIVER

Deliver verified datasets.

Get production-ready datasets, with every annotation carrying its permanent Mango Trail record.

Mango trail

Every annotation,
on the record.

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
MANGO TRAIL RECORDSEALED · IMMUTABLE
NODULE · 8MM✓ Verified

ANNOTATION

#MT-048291

✓ Verified

SPECIALTY

Radiology

REVIEW

Second review passed

PROJECT

Lung Nodule Detection Dataset

Verified Annotator✔Radiology specialist✦ RADIOLOGIST
Identity VerifiedCredentials VerifiedSpecialty Verified

ANNOTATION LINEAGE

HOVER A NODE

Built for teams

Built for teams building the
future of healthcare AI.

Verified

Credentials checked at the primary source before any work begins.

Traceable

Each label carries the identity of the clinician who produced it.

Reviewed

Every annotation passes through structured quality assurance.

Specialized

Experts are matched to projects based on medical specialty.

Accountable

Know who created every data point and how it was reviewed.

Secure

Enterprise-grade identity verification protects every project.

Data types

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

Evaluation, 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.

De-identification

PHI detection and redaction, so your data is safe before it's ever labeled.

Built for teams
advancing healthcare AI.

Healthcare AI companies

Train production-ready clinical models on verified, expertly labeled medical data.

Medical-device and SaMD teams

Get training data whose provenance holds up to FDA scrutiny, every label tied to a verified specialist.

Medical imaging companies

Scale annotation without trading away quality, accuracy, or the proof of who did the work.

Research institutions

High-quality labels from qualified medical experts, with a record you can publish and defend.

Hospitals and health systems

Verified clinical annotation, done for you, as you build your own clinical AI.

Pharmaceutical companies

Expertly annotated data for drug discovery and clinical research.

Better healthcare AI
starts here.

Build expert-reviewed datasets with verified medical professionals, enterprise-grade quality assurance, and complete annotation traceability.

Annotated clinical documents on a desk