The most valuable medical knowledge isn't written down — it lives in how physicians reason. SinoHealth AI is a verticalized data & environments research lab for medical AI: we turn clinical judgment into evals, RLHF, de-identified datasets and reasoning environments — physician-in-the-loop and compliant. Singapore-based, serving medical AI worldwide.
Real clinical judgment — the differentials, the follow-up questions, the safety instincts — isn't written down. It lives in how physicians think. We capture it, and turn it into data models can learn from.
Models trained on outputs plateau. Models trained on reasoning improve.
Leading LLMs do fine on clean case notes, but break on patients' real, incomplete accounts. Fixing that starts with data only practicing physicians can produce — measured, structured, and compliant.
Every task is handled by attending-level specialists with verified credentials, drawn from a global clinical network — not generic labelers.
Dual annotation → senior adjudication → gold-set audit, with Cohen's kappa monitored throughout. Quality is measurable and traceable.
De-identification, ethics review and configurable data residency, aligned with HIPAA, GDPR and PDPA — compliance is built into the pipeline.
Ingest raw clinical data through compliant channels; de-identify and normalize to a clean, structured base.
Physicians structure, label, and build eval / RLHF data; dual annotation with senior adjudication and kappa.
Gold-set audit and double-blind review, then delivery as JSONL + spec + QA report, in your language.
We go beyond labeling: we identify where medical models fail, build the data and rubrics to fix it, verify the gains, and publish — a loop where every turn compounds the next.
Construct realistic, challenging clinical tasks that surface where models fail.
Physicians build targeted data, rubrics and environments for each failure mode.
Post-train and verify the signal measurably improves models.
Publish open results — credibility and inbound demand.
Model builders license the data and evaluations behind the results.
The starting point of our flywheel — an open benchmark for physician-grade clinical reasoning and safety, spanning specialties and languages.
Spec, scoring rubric and worked samples are ready to demo against your model's evaluation needs.
We move medical data from raw resource, to standardized data product, to deployed application — physician-in-the-loop and compliant at every layer.
Compliant access + de-identification + structuring of clinical, imaging and lab data (China & global sources).
Standardized, documented datasets, eval sets and RLHF data — with transparent rights & provenance.
Deploy clinical AI — e.g. a hospital consultation agent (software + hardware) — into partner hospitals.
End-to-end data pre-processing for medical AI — from raw records to model-ready datasets, every step delivered by practicing physicians.
De-identification, cleaning, structuring and normalization (ICD coding) of raw clinical data into model-ready datasets.
Clinician-in-the-loop labeling across clinical text and imaging — entity, relation, diagnosis and reasoning labels.
Physicians score, rank and rewrite model outputs into clinically-grounded preference and SFT data.
Diagnostic-reasoning, safety and guideline-alignment evals that quantify how a model actually performs.
Adversarial testing for medical safety — surfacing unsafe advice, hallucination and missed red flags before your users do.
Radiology and pathology specialists for image labeling, report-quality assessment and image-text alignment.
Tell us your model, use case and evaluation goals; we'll return an actionable plan and quote.
Not one-off labeling — standardized, documented data products with transparent rights and provenance. Every product states its source, processor and licensed use.
Tell us your model, task and target metrics — we'll scope a product with a full spec, rights statement and quote.
Every product ships with a data dictionary and a rights & provenance statement (source institution · processor · licensed use). Figures are illustrative and confirmed at scoping.
Different teams need different things from clinical data. We tailor products and services to each.
Evals, RLHF, de-identified corpora and fine-tuning data to make models reason and stay safe.
De-identified real-world & imaging datasets for research, biomarker and model development.
Co-develop a dedicated consultation agent (software + hardware) that lifts physician efficiency.
Structured clinical data and evals for underwriting, claims and health-management models.
Each specialty is staffed with practicing specialists from our global network and matched to high-value tasks.
Diagnostic-reasoning & treatment eval, guideline alignment, staging and drug checks.
Lesion annotation, report-quality scoring, image-text alignment.
Red-flag detection, differentials, ECG-imaging combined eval.
Chronic-care pathways, family-doctor eval, medication labeling.
Information-seeking checks, differential correction, imaging-symptom integration.
Pediatric disease labeling, dosage safety, growth assessment.
Neuro differentials, imaging annotation, scale-based assessment.
Pathology image labeling, diagnostic-concordance scoring, structured reports.
End-to-end clinical decision support, red-flag safety eval, triage pathways.
From physician credentials to delivery, every step has standards and metrics — and data is compliant across the jurisdictions you operate in.
Attending-level and above; licenses and specialty backgrounds are strictly verified before onboarding.
Each record is annotated independently by two physicians to avoid single-rater bias.
Disagreements escalate to senior experts, forming the gold version.
Cohen's / Fleiss' kappa is monitored throughout; below threshold triggers a calibration session.
Known-answer items seeded per batch; ≥20% double-blind review before delivery.
De-identification, ethics/IRB review and configurable data residency across jurisdictions.
De-identification, DPAs, and data-residency options are configured per client and jurisdiction.
Join SinoHealth AI's global network of licensed physician experts — remote, flexible, paid per project — and shape the evaluation and training data behind frontier medical AI.
Work online on your own schedule, alongside clinical practice.
Paid by expert-hour; scarcer specialties earn more.
Directly shape evaluation and alignment for leading medical AI.
Define the clinical bar for AI with your specialist judgment.
Fill in the form with your specialty and practice details.
We verify your license and you complete a short trial task.
Get matched to projects by specialty, paid by the hour.
Your application is emailed to us; we'll reach out after verification.
In collaboration with medical schools and hospitals in China and abroad, we combine their clinical resources with our data to research and build a hospital-specific consultation agent — software and hardware — that helps physicians work faster.
We co-develop with each partner: their specialists and research capacity, our de-identified data and physician-annotation methodology, delivered as a system the hospital owns.
Clinical expertise and research capacity from partner medical schools and their affiliated hospitals.
De-identified, multi-source clinical data and reproducible physician annotation — the fuel a reliable agent needs.
A consultation agent tuned to the hospital's specialties and workflow, delivered as an integrated software-and-hardware system.
Structured history-taking before the visit, so physicians start with a clear picture.
The agent asks the right clarifying questions instead of jumping to conclusions.
Drafts notes and summaries, cutting time spent on paperwork.
Guideline-aligned suggestions with safety and red-flag checks, physician-in-command.
Tuned to the hospital's departments, pathways and language.
Assists, never replaces — the clinician stays in control at every step.
We're in discussions with several institutions in China and abroad. Tell us about yours.
SinoHealth AI is a Singapore-based verticalized data & environments research lab for medical AI, serving model builders worldwide. We pair SinoHealth's clinical network with a global roster of expert physicians.
We believe the ceiling of medical AI is set by how much real clinical judgment lives in its data. So we embed physicians in every step — sourcing, structuring, annotation, RLHF, evaluation and reasoning environments — with reproducible QA and compliance built in.
Leave your details and we'll share a clinician-grade eval sample and a one-pager, then set up a 20-minute call.
Submissions are emailed to bryson@sinohealth.ai; we'll reply shortly.