Access qualified medical expertise for AI evaluation, clinical reasoning, safety testing, expert data creation, multilingual projects, and specialized medical-AI workflows through one managed relationship.
Clinical review and structured assessment of AI outputs.
Qualified physicians review model outputs for clinical accuracy, reasoning, relevance, consistency, and usefulness. Evaluation can cover single-turn answers, multi-step clinical reasoning, and comparisons between candidate responses.
Physician review of model outputs against expected clinical standards
Structured assessment of diagnostic and treatment reasoning
Identification of errors, gaps, and inconsistencies in medical content
Expert judgment on whether an output is appropriate for its intended use
Safety
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Expert identification of potentially unsafe model behavior.
Experts review and probe AI behavior for outputs that could be unsafe, misleading, incomplete, or clinically inappropriate, with findings organized so they can inform model improvement.
Identification of unsafe, misleading, or clinically inappropriate outputs
Review of edge cases where models may give harmful or incomplete guidance
Assessment of how systems handle urgent, ambiguous, or high-risk scenarios
Structured reporting of safety-relevant findings
Expert Data
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Physician-generated data that reflects real clinical judgment.
Experts create and label the medical data AI teams need: annotations, reference answers, rubrics, structured feedback, and evaluation datasets grounded in genuine clinical expertise.
Expert annotations and labeling of medical content
Reference answers grounded in clinical knowledge
Rubrics and criteria for evaluating medical-AI performance
Structured expert feedback on outputs, data, and workflows
Medical Content
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Expert-authored and reviewed medical material.
Physicians develop and review the medical substance of a project: questions, cases, explanations, and assessment material that must be accurate, clear, and appropriately calibrated.
Expert-authored medical questions, cases, and scenarios
Explanations and rationales reviewed for clinical accuracy
Assessment material for training and evaluating medical-AI systems
Review and correction of existing medical content
Multilingual & Local Context
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Evaluation grounded in language and real care environments.
Medical AI must work across languages and healthcare settings. Experts evaluate systems in the languages and clinical environments relevant to each project, including contexts where resources, workflows, and communication differ from textbook settings.
Evaluation involving English, Amharic, Tigrinya, Oromo, and other network languages
Review of outputs for linguistic and clinical appropriateness
Local clinical context: healthcare resources, workflows, and patient environments
Insight for systems serving diverse or resource-constrained settings
Why Linco
Expertise matched to the work.
Medical-AI projects require more than access to physicians. They require qualified expertise aligned with specialty, experience, language capabilities, project requirements, and delivery needs.
Specialized expertise
Access physicians across primary care and medical specialties.
Multilingual capability
Support medical-AI workflows involving multiple languages and clinical contexts.
Managed delivery
Work through one managed relationship rather than coordinating multiple experts independently.
Engagement
Flexible engagement for different project needs.
Expert capacity is structured around each engagement. The appropriate commercial and delivery model depends on the expertise, complexity, volume, duration, and project requirements.
Expert Capacity
Access defined medical expert capacity for ongoing or time-bound workflows.
Project Cohorts
Build specialized groups of physicians around a project, specialty, language, or use case.
Project Delivery
Engage Linco for defined evaluation, expert-data, content, safety, or other medical-AI deliverables.
How to engage
Start with the requirement.
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Tell us what you need.
Share your project, expertise, specialty, language, capacity, and timeline.
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We assess the fit.
Linco reviews the requirement against available expertise and current capacity.
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We shape the engagement.
We propose an appropriate expert capacity or project delivery structure.
Clinical AI evaluation, clinical reasoning assessment, AI safety testing, expert data creation, medical content, multilingual workflows, and other medical-AI work requiring qualified medical expertise.
Generalist and primary-care expertise alongside medical specialties. Available expertise depends on the project and current expert capacity.
Yes. Current capabilities include English, Amharic, Tigrinya, and Oromo, with language requirements and available coverage assessed for each project.
Yes. Generalist and primary-care expertise is a core part of the network, alongside medical specialties.
Yes. Linco can structure a specialized group of physicians around a project, specialty, language, or use case.
Experts complete a structured qualification process covering credentials, clinical expertise, safety judgment, and project readiness. Learn more about the Expert Network.
Yes. Pilot engagements are considered subject to current expert capacity and project fit.
Tell us what expertise your project requires.
Share your requirements for an assessment of current expert fit, capacity, and potential next steps.