The graph behind Gabriel's reasoning.
This is the layer that makes chat useful. Gabriel connects curated clinical sources, structured condition logic, practitioner context, diagnostics, and protocol safety into one reasoning system.
One intelligence layer connecting evidence, care, and action.
Explore the knowledge graph itself.
Rotate, zoom, and inspect how conditions, diagnostics, practitioners, and protocols connect inside Gabriel's reasoning layer.
The layer that makes one prompt useful.
A chat bar only matters if the system behind it can actually reason. Gabriel's graph is where evidence, cross-tradition logic, safety checks, and real next steps stay connected.
Curated corpus
Books, papers, transcripts, and traditional medicine systems are selected, tagged, and connected instead of scraped into one undifferentiated pile.
Cross-tradition links
Conditions, treatments, diagnostics, symptoms, and labs are connected so Gabriel can reason across modalities instead of answering inside one silo.
Evidence weighting
Recommendations inherit evidence strength, safety context, and practical next steps so answers stay attached to the real support behind them.
Action layer
The same graph powers practitioner search, diagnostic comparison, protocol building, and the app's follow-through layer.
Evidence, fit, and execution stay attached.
The graph is not just storage. It is the layer that keeps practitioner fit, evidence strength, protocol safety, and next actions connected inside the same answer.
Gabriel Brain Score
Resources are weighted for study quality, mechanism plausibility, clinical use, historical use, and real-world relevance before they influence an answer.
Practitioner GPS
Credentials, patient trust, and treatment fit are scored together so practitioner discovery stays connected to the same reasoning layer.
Protocol trust chain
Interactions, contraindications, evidence grading, and next-step logistics stay attached when Gabriel turns reasoning into action.
A smarter system does not need to feel extractive.
Gabriel is designed so members can get value quickly, add more context only when they want to, and keep the platform working on their behalf instead of against them.
You choose what to connect
Wearables, labs, and test results are optional. Gabriel can answer a question immediately, then go deeper if you decide to add more context.
Reasoning stays safety-aware
Interaction checks, contraindications, and evidence levels stay attached to the answer instead of being split into separate tools.
Member-first by design
Gabriel is built to serve the member, not to harvest or sell health data. The platform is designed around control, context, and consent.
Explore the system by asking a real question.
The graph matters because it changes what Gabriel can do in chat, in diagnostics, in practitioner discovery, and in the app's action layer.