Gabriel Brain
Health intelligence that sees the whole picture.
Gabriel connects the health context you choose to share, reasons through what matters, and helps move the next step forward.
One question. Connected context.
See what changes the answer.
Choose a sample question. The map shows how different kinds of member context can shape pattern recognition, evidence, safety, and the next step.
Representative intelligence map
Choose a question to see how different kinds of context can change the path.
Member context
“Why does my energy fall apart every afternoon?”
Useful output
This visualization uses synthetic examples to explain system behavior. It is not a live view of member data, internal prompts, model reasoning, or production infrastructure.
Built differently
Not a wrapper. A health intelligence stack.
The conversation is the surface. Underneath it, Gabriel combines model-agnostic orchestration, proprietary health intelligence, structured reasoning, and specialized tools.
6.2M+
Indexed research vectors
A proprietary, deep-and-narrow health corpus built for precise retrieval.
Model-agnostic
Reasoning and orchestration
The best-fit model can change without changing Gabriel or the member experience.
Fine-tuned
Sovereign specialist model
A completed local health model provides an owned capability held in reserve.
Structured
Clinical intelligence
Reasoning pathways and specialized tools add discipline beyond free-form generation.
Two-layer intelligence
Conscious judgment. Subconscious depth.
Gabriel separates the work of understanding and communicating from the deeper retrieval and specialist analysis that support it.
Conscious layer
Judgment and orchestration
Understands the member, decides what deserves investigation, selects the right context, model, and tools, then communicates the answer clearly.
Subconscious layer
Depth and specialization
Retrieves focused domain evidence and supports specialist analysis behind the conversation, including a fine-tuned sovereign model capability.
Relevant history, not a blank chat
Vector retrieval can surface useful context from the member's evolving Record when it changes the answer.
Structured paths through complex questions
Clinical reasoning pathways help identify what is missing, what is uncertain, and what needs professional review.
The right capability for the job
Gabriel can coordinate purpose-built tools for evidence, labs, interactions, diagnostics, practitioners, insurance, and care.
An answer that can move work forward
Evidence, safety boundaries, and the next useful action stay connected, with approval preserved where it matters.
Corpus scale reflects the verified production index as of July 2026. Architecture descriptions are intentionally conceptual. Production prompts, model routing, reasoning thresholds, tool schemas, clinical taxonomies, and private infrastructure remain proprietary.
The difference is continuity.
Most AI answers the prompt. Gabriel is designed to keep the health thread connected.
Remembers
Useful context can stay attached to the member instead of disappearing after one answer.
Connects
Symptoms can be considered alongside labs, medications, supplements, wearables, genetics, and history.
Follows through
Gabriel can help prepare the next step, organize care, and support approved actions across surfaces.
Intelligence should increase your control.
Start with a question. Add more context only when it helps. Sensitive or consequential actions preserve the approval and professional-care boundaries required for that workflow.
Your context is optional
Uploads and connected health sources remain choices, not prerequisites.
Safety stays attached
Interactions, red flags, uncertainty, and professional-care needs remain part of the answer.
Approval stays visible
Supported external actions retain the confirmation and consent required for the task.
Start with a real question
Tell Gabriel what is going on.
You do not need to understand the system to use it.