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Karmyug

Clinical data reviewed by people with the credential to review it.

Medical imaging, clinical NLP and consultation transcription.

A pathology label from a crowd worker is worse than no label, because it looks like data. Clinical annotation needs clinicians, and clinicians need a workflow that respects their time.

We route imaging and record work to verified practitioners, run consensus on contested findings, and report agreement per finding rather than per study.

Where AI is being applied in healthcare

The applications teams actually come to us for, rather than the full theoretical list.

  • Medical imaging

    X-ray, CT and MRI annotation for detection and segmentation.

  • Clinical NLP

    Entity, medication and history extraction from records.

  • Consultation transcription

    Doctor and patient audio transcribed with correct terminology.

  • Doctor dictation

    Dictation corpora for ambient documentation models.

  • Patient support chat

    Triage and appointment dialogue in regional languages.

  • De-identification

    Spoken and written PII removal with a verification pass.

Data security and compliance

The controls your risk team will ask about, before they ask.

  • GDPR

    EU data subject rights and DPAs

  • CCPA

    California consumer privacy

  • DPDP Act 2023

    India data protection, in-region storage

Healthcare questions

Do you work under HIPAA?

We run a HIPAA-aligned workflow with BAAs where the engagement requires it, and keep clinical data inside a restricted pool.

Who annotates clinical data?

Verified clinicians and trained medical annotators, with credential checks recorded per contributor.

Power your healthcare AI with data you can audit.

Start with a pilot batch against your real guidelines. You accept it before anything scales.