Clinical AI data built for
programs that cannot fail.
When a model touches diagnostic decisions, the annotation workforce matters as much as the architecture. We provide credentialed medical annotators, ISO-certified data security infrastructure, and in-country clinical coverage across 155+ locales.
Where clinical AI programs break down.
Most data annotation vendors were built for general-purpose AI. Clinical AI has different requirements at every layer: annotator credentials, data handling compliance, and multilingual clinical terminology. These are not edge cases.
Annotation without clinical credentials
ICD code classification, imaging landmark annotation, and clinical NER require annotators with medical backgrounds. Without credential verification, labeling error rates compound across training cycles in ways that are difficult to audit and expensive to fix.
Patient data handling without appropriate security infrastructure
Patient and health data requires more than an NDA. Audit-ready de-identification workflows, ISO 27701 privacy management, and appropriate data handling frameworks must be built into the pipeline architecture, not bolted on.
Clinical coverage limited to English
Medical terminology does not translate literally across languages. Models trained on English-only clinical data fail in international deployments. In-country annotators with native-language medical knowledge are the only reliable path to global clinical AI.
Use cases for clinical AI teams.
Medical Imaging Annotation
Bounding box, polygon, and landmark annotation of radiology, pathology, and ophthalmic images by credentialed annotators. Supports DICOM formats across CT, MRI, and ultrasound with modality-specific quality protocols.
Clinical NER and ICD Coding
Named entity recognition and ICD-10/SNOMED-CT classification applied to discharge summaries, referral letters, and clinical notes. Structured for downstream coding automation and clinical decision support pipelines.
Patient-Facing Conversational AI
Intent and entity annotation for virtual care assistants and patient-facing chatbots, including symptom slot-filling, medication intent, and appointment scheduling across 155+ locales.
Reinforcement Learning from Medical Feedback
Physician and specialist reviewers evaluate model outputs against diagnostic accuracy, clinical reasoning quality, and guideline alignment, producing structured feedback for RLHF fine-tuning cycles.
Patient Data De-identification
Systematic redaction and anonymization of patient-identifiable information from clinical notes, imaging metadata, and structured records. Workers operate only on de-identified content, with full audit trail.
Clinical Trial and Real-World Evidence Annotation
Adverse event coding, eligibility criteria tagging, and outcome classification applied to clinical trial datasets and real-world evidence collections for regulatory-ready AI training data.
Clinical data types we annotate.
Medical Imaging
DICOM radiology scans (CT, MRI, X-ray), pathology slides, retinal imaging, ultrasound video, and surgical footage annotated with landmark, segmentation, and bounding box protocols.
Clinical Text
Electronic health records, discharge summaries, clinical notes, referral letters, and prescription data annotated with medical NER, ICD-10 coding, and clinical classification.
Speech and Audio
Patient-clinician interactions, telehealth session recordings, and EHR voice dictation annotated for intent, terminology accuracy, and transcription quality across 155+ locales.
Multimodal Clinical Data
Combined imaging and text datasets for diagnostic AI, including radiology report grounding, histopathology slide-to-report alignment, and genomic data structuring.
Four reasons clinical AI teams choose Welo Data.
Credentialed annotators, verified through NIMO before production access.
Every clinical program is staffed to the credential level the task requires: annotators with medical imaging backgrounds for radiology annotation, clinical documentation specialists for NER, life sciences researchers for genomic data. Credentials are verified through our NIMO identity platform before any production access is granted.
ISO 13485 and data security compliance built into the pipeline.
Our data handling pipelines are designed around GDPR, FDA SaMD, and applicable data protection requirements from architecture through delivery. ISO 13485:2016 medical device quality certification governs clinical programs. For programs involving patient data, we structure workflows so workers operate only on de-identified content.
NIMO: continuous identity and quality assurance at the annotator level.
Our NIMO platform monitors 130+ behavioral and identity variables per contributor throughout every production program. KYC, OFAC checks, adverse media screening, and continuous behavioral monitoring run in parallel to annotation, not as a pre-program gate.
155+ locales with in-country clinical expertise.
Clinical AI deployed globally fails when built on translated annotation guidelines. We staff every locale with in-country annotators who have native-language medical domain knowledge, covering 155+ locales across clinical text, imaging review, and conversational AI programs.
What clinical AI buyers ask us.
For programs involving patient or health data, we structure workflows so contributors operate only on de-identified or redacted content. Workers never have visibility into identifiable patient information. ISO/IEC 27701:2019 privacy information management governs all data handling. ISO/IEC 27001:2013 provides the security certification framework. Audit-ready documentation is a standard deliverable. For clients requiring full HIPAA Business Associate Agreement coverage, we work with legal and compliance teams to establish the appropriate contractual and operational framework for each program.
We match annotators to task requirements: radiology and imaging annotation by annotators with medical imaging and clinical backgrounds; clinical NER by medical documentation and nursing professionals; genomic and life sciences tasks by researchers with relevant academic or clinical backgrounds. All backgrounds are verified through our NIMO platform prior to production access.
We staff every locale with in-country annotators who have genuine native-language medical knowledge. We do not translate English annotation guidelines across markets. Each language program is built from ground-level clinical expertise in that language, covering 155+ locales.
On-site deployments with security onboarding can be fully operational within 4 weeks. Distributed multilingual clinical programs spanning 24+ languages reach full production capacity within 2 months. Our contributor pool maintains a pre-screened base of credentialed medical annotators across all major clinical specialties.
Yes. Clinical data programs are structured to produce audit-ready documentation aligned with Software as a Medical Device validation requirements. ISO 13485:2016 governs our medical device quality management processes, and program deliverables are structured to support FDA and EMA regulatory submissions.
Clinical AI data that holds up under regulatory scrutiny.
Credentialed annotators. ISO-certified data security. 155+ locales with in-country clinical expertise.