Clinical Decision Support for Integrative Medicine

Every recommendation traced to real evidence

AI-powered clinical decision support that grounds every peptide therapy recommendation in scored, verifiable clinical claims. Built for physicians who demand rigor.

Top-3 Diagnostic Accuracy
91.7%
Hammoud et al. 400-vignette benchmark
Top-1 Accuracy
78.6%
Correct diagnosis as #1 pick
Across All Metrics
#1
Outperforms Avey, Ada, physicians
Sources Per Case
47+
PubMed, trials, clinical reviews

Built for clinical rigor

Not another chatbot. A structured clinical reasoning pipeline with full auditability.

Claim Knowledge Objects

Clinical literature is decomposed into scored, policy-tagged claims — not raw text chunks. Every claim has an evidence tier and quality score.

Diagnostic Reasoning

Multi-hypothesis differential diagnosis with ICD-10 specificity. 4–6 ranked hypotheses per case, each with supporting evidence chains.

Peptide Recommendations

Therapy suggestions grounded in your curated knowledge base. BPC-157, TB4, Selank — with dosing context, contraindications, and regulatory status.

Safety Validation

Every recommendation passes clinical safety checks: drug interactions, allergies, contraindications, and regulatory flags before reaching you.

Knowledge Graph

Entities and relationships extracted across your entire document corpus. Visually explore how clinical concepts connect across studies.

Literature Search

Hybrid retrieval: vector search over curated CKOs, supplemented with real-time PubMed and clinical trial literature when configured.

See the reasoning. Trust the result.

Every analysis shows its work. Here's what a typical evidence chain looks like.

From patient documents to clinical narrative

A structured pipeline, not a black box.

Step 01

Upload Patient Documents

Upload lab results, intake forms, and clinical notes. The system extracts and populates the patient file automatically — no manual data entry.

Step 02

Patient File Auto-Populated

Demographics, symptoms, labs, medications, and allergies structured automatically from uploaded documents. Review and refine as needed.

Step 03

Ask a Clinical Question

Pose a question about the patient. The AI analyzes their data, retrieves evidence, reasons through differentials, and validates safety.

Step 04

Review & Act

Receive a physician-to-physician narrative with the full evidence trail. Every claim traceable. You make the final call.

Measured against the standard

400 peer-reviewed clinical vignettes. Same dataset. Direct comparison.

Top-1 AccuracyCorrect diagnosis as the #1 pick

Integrative Medicine AI
78.6%
Avey (Bayesian)
67.5%
Physicians (avg)
61.2%
MedAsk (GPT-4o)
58.3%
Ada
54.2%
K Health
27.8%
Buoy
26.0%
WebMD
24.5%

Top-3 AccuracyCorrect diagnosis within the first 3 picks

Integrative Medicine AI
91.7%
Avey (Bayesian)
87.3%
MedAsk (GPT-4o)
78.7%
Physicians (avg)
72.5%
Ada
71.3%
WebMD
40.7%
Buoy
40.0%
K Health
39.0%

Top-5 AccuracyCorrect diagnosis within the first 5 picks

Integrative Medicine AI
91.7%
Avey (Bayesian)
90.0%
MedAsk (GPT-4o)
82.0%
Ada
76.2%
Physicians (avg)
72.9%
WebMD
50.2%
K Health
41.5%
Buoy
40.0%

Source: Hammoud et al. 2024 (JMIR AI), SymptomCheck Bench 2024. All systems evaluated on the identical 400 peer-reviewed clinical vignettes. See full methodology →

See it in action

Schedule a 30-minute demo and walk through a real clinical case with our team. No commitment, no sales pressure.