When AI Specialists Debate Your Case, Blind Spots Disappear
Roundtable puts Claude, GPT-4, Gemini, and Grok on the same clinical consultation — one generates the differential, another challenges it, while pharmacology and evidence experts add context. Multi-specialty reasoning in minutes, not weeks.
One Case. Every Specialty Heard.
Unlike single-model AI, Roundtable runs multiple models in parallel — and they can see and challenge each other's clinical reasoning.
Debating
Models surface genuine disagreements about differential diagnosis and treatment approach.
Analyzing
Models examine cases from different specialty angles, challenging each other's assessments.
Brainstorming
Models explore creative diagnostic hypotheses and novel treatment combinations.
Problem Solving
Models build toward actionable workup plans and evidence-based treatment recommendations.
You choose the mode. You assign the specialties. The models do the rest — and a Council Moderator synthesizes the consensus at the end.
Clinical Reasoning Is the Bottleneck
UpToDate gives you the guidelines. PubMed gives you the literature. But the critical reasoning layer — synthesizing symptoms, differentials, drug interactions, and evidence into a clinical plan? That still happens in the clinician's head, alone.
Reference Content
UpToDate, PubMed, DynaMed
Clinical Reasoning
Manual. Hours to days per complex case.
Documentation
Nuance DAX, Epic, Cerner
12 million diagnostic errors every year in the US alone.
Complex cases need multi-specialty input. But specialist wait times average 3-4 weeks, and clinicians have 15 minutes per appointment. The math doesn't work.
Built for Clinicians Who Need Answers Now
Whether you're preparing for tumor board, working up a complex case, or teaching clinical reasoning — the need is the same: multi-specialty perspective, fast.
Hospital Systems
Tumor board prep takes hours. Complex cases need multi-specialty input but specialist access is limited. Diagnostic errors affect patient outcomes and create liability.
Diagnostic error and specialist accessClinicians
15-minute appointments to evaluate complex presentations. Specialist wait times average 3-4 weeks. Literature keeps expanding faster than any one person can track.
Cognitive overload and time pressureMedical Educators
Case-based learning requires showing how different specialists approach the same problem. Building realistic multi-perspective clinical scenarios is time-intensive.
Teaching clinical reasoning at scaleClinical Researchers
Literature synthesis across therapeutic areas takes days. Evidence evaluation requires checking multiple guidelines, meta-analyses, and clinical trial databases.
Literature synthesis bottleneckWhy Asking ChatGPT for a Diagnosis Doesn't Work
Generic AI can list symptoms. But clinical reasoning demands adversarial differential thinking, evidence grading, and multi-specialty challenge that a single model cannot deliver.
Anchoring Bias
A single model anchors on the most likely diagnosis and fails to adequately weigh rare but dangerous alternatives. In clinical reasoning, the differential diagnosis exists precisely because anchoring kills — the zebra you didn't consider is the one that harms the patient.
Hallucinated Medical Citations
LLMs fabricate study references, drug dosages, and guideline recommendations. In clinical contexts, a hallucinated drug interaction or fabricated contraindication doesn't just waste time — it can directly harm patients. Clinical reasoning demands verifiable, citation-backed evidence.
Single-Specialty Blindness
Complex presentations require simultaneous input from primary care, specialty medicine, pharmacology, and evidence-based medicine. A single model produces one perspective — but clinical reasoning requires the tension between specialties to surface the right diagnosis.
Roundtable fixes this. When a Primary Care Physician and Specialist Consultant debate the same case — and a Pharmacist and Evidence Reviewer add context — anchoring bias gets caught, citations get verified, and the differential gets stress-tested.
Multiple Specialists Catch What One Misses
A single AI gives you a diagnosis. But when Primary Care, Specialist, Pharmacist, and Evidence Reviewer models debate the same case — anchoring bias gets caught, rare diagnoses get considered, and drug interactions get flagged.
Cross-Specialty Challenge Saves Lives
When the PCP anchors on lymphoma, the Specialist can push for myeloma workup. When both miss a medication interaction, the Pharmacist catches it. Anchoring bias doesn't survive multi-specialty cross-examination.
Multiple Specialties, Full Picture
A symptom cluster means different things to different specialties. When primary care, specialty, pharmacology, and evidence-based medicine perspectives all weigh in, the picture becomes three-dimensional.
Synthesis Through Consultation
Symptoms, labs, medications, and guidelines need cross-referencing. When models respond to each other, they naturally connect dots across clinical domains that siloed reasoning misses.
Assign Specialties. Start the Consultation.
In Roundtable, you pick the AI models and assign each one a medical specialty — just like convening a real clinical consultation. Here's a setup clinicians use for complex cases:
Primary Care Physician
ClaudeInitial assessment, differential diagnosis generation, workup planning, and referral triage.
Specialist Consultant
GPT-4oDomain-specific deep dive — cardiology, oncology, neurology, or any subspecialty your case requires.
Pharmacist
GeminiDrug interactions, dosing verification, contraindications, and medication reconciliation.
Evidence Reviewer
GrokLiterature search, clinical trial relevance, guideline concordance, and evidence grading.
Differential Diagnosis
Multi-specialty differential diagnosis with evidence-based reasoning and workup planning.
Treatment Planning
Treatment protocol evaluation, guideline concordance, and patient-specific therapy planning.
Drug Interaction Review
Comprehensive medication review, interaction checking, and polypharmacy risk assessment.
Clinical Case Conference
Virtual tumor board or clinical case conference with multi-specialty deliberation.
Weeks of Specialist Access → Minutes of AI Consultation
From case presentation to structured multi-specialty reasoning.
- 1Patient presents with complex symptoms (15-minute visit)
- 2Review history, order initial labs (30-60 minutes)
- 3Consult specialists — wait 3-4 weeks for availability
- 4Literature review for differential (1-2 hours)
- 5Synthesize findings and finalize treatment plan (variable)
- 1Describe the case presentation and relevant history
- 2AI specialists analyze in parallel — each from their domain
- 3Council Moderator synthesizes consensus with evidence citations
- 4You review the reasoning and make clinical decisions
Clinical AI Has Reached an Inflection Point
Google\'s Med-PaLM 2 achieved expert-level performance on medical exams. Glass Health raised $17M for AI differential diagnosis. The clinical AI market is accelerating.
12M
Americans affected by diagnostic errors annually
BMJ Quality & Safety
86%
of physicians believe AI will be part of clinical practice within 5 years
AMA Physician Survey
$22.4B
projected clinical AI market size by 2028
MarketsandMarkets
Mayo Clinic, Johns Hopkins, and Mount Sinai are deploying AI clinical decision support. The American Medical Association reports that 86% of physicians expect AI to be part of clinical practice within 5 years.
"AI will not replace physicians. But physicians who use AI will replace physicians who don\'t."
A Consultation Team That Never Gets Tired
The same rigor on the last patient as the first.
Complete Differential
Get structured multi-specialty reasoning for every complex case. When 4 AI specialists work in parallel, no diagnosis goes unchallenged.
Speed to Diagnosis
Multi-specialty AI consultation in minutes, not weeks. Immediate structured reasoning supports faster workups and more targeted referrals.
Consistent Reasoning
Every case gets the same multi-specialty rigor — whether it's the first patient of the day or the last. No cognitive fatigue, no anchoring drift.
Built for Clinical Confidence
Roundtable is designed for high-stakes clinical reasoning — where every recommendation must be traceable, evidence-based, and ultimately validated by a qualified clinician.
Full Traceability
Every insight links to the model that produced it and the evidence it cited. No black-box diagnoses — every recommendation has a reasoning trail.
Your Data Stays Yours
Your data stays private. API traffic is excluded from model training by our providers. All infrastructure runs on Cloudflare's encrypted global network. Use de-identified data for maximum privacy.
Human-in-the-Loop
AI is the consultation team. You're the clinician. Roundtable provides structured reasoning to support your judgment — it never makes autonomous clinical decisions.
Important Disclaimer
Roundtable is an advisory and educational tool. It does not replace clinical judgment, is not a medical device, and should not be used as a substitute for professional medical advice, diagnosis, or treatment. All clinical decisions must be made by qualified healthcare professionals.
Frequently Asked Questions
Your AI Clinical Consultation Is Ready
Assign the specialties. Pick the models. Describe the case. Whether it's differential diagnosis, treatment planning, or any clinical question that deserves more than one perspective — Roundtable makes sure nothing gets missed.