Healthcare: Clinical GraphRAG & Decision Support
Clinical GraphRAG: AI answers grounded in your data: measurable hallucination reduction.
Ground every LLM answer in your clinical knowledge graph and the patient's record, with fact level citations your compliance team can click. Guaranteed hallucination reduction, in writing.
The short answer
What is clinical GraphRAG, and how does it reduce hallucinations?
GraphRAG (graph retrieval augmented generation) is a technique that grounds a large language model in a knowledge graph rather than a plain vector store. In a clinical setting, the model can only cite entities that exist in your graph (guidelines, drug references, and the patient's structured record) and every fact carries provenance back to its source system. Because the answer is constrained to real, connected data, hallucination rates drop measurably versus vector only baselines. That's why we guarantee the agreed reduction target in writing.
What we build
Clinical GraphRAG & Decision Support, engineered on your data.
Knowledge graph grounding
Answers are constrained to entities and relationships that exist in your graph: the model can't invent a drug, dose, or guideline that isn't there.
Fact level citations
Every answer ships with citations to the exact guideline section and patient record fields it used, so a clinician or auditor can verify it.
Clinical guardrails
Guardrails against out of formulary, contraindicated, or off guideline recommendations, tuned by graph context rather than global rules.
Ambient documentation & AI scribe
Draft SOAP notes and summaries grounded in the encounter and record, with the source of every statement traceable.
CDS Hooks integration
Surface grounded decision support inside the EHR workflow via CDS Hooks and SMART on FHIR, at the moment of decision.
Private, on prem LLMs
Run GraphRAG on open weight models (Llama, Mistral) in your VPC or on prem so PHI never leaves your infrastructure.
FAQ
Clinical GraphRAG & Decision Support: frequently asked questions.
What's the difference between RAG and GraphRAG in healthcare?
Standard RAG retrieves text chunks by vector similarity and hopes the model uses them faithfully: it can still hallucinate or blend sources. GraphRAG retrieves connected entities from a knowledge graph, so the model reasons over structured, related facts (this patient, this condition, this medication, this guideline) and every claim traces to a source. For clinical use, that structure is the difference between an answer you can cite and one you can't.
Is clinical GraphRAG HIPAA compliant?
Yes. We run GraphRAG on open weight models inside your VPC or on prem so PHI never leaves your walls, with BAAs, property level access controls, encryption, and full query audit logging: SOC 2 Type II. When a public LLM API is in scope, we use zero retention agreements and a PHI de identification layer.
What is an AI medical scribe, and does it hallucinate?
An AI medical scribe drafts clinical documentation (like SOAP notes) from the encounter so clinicians spend less time typing. The risk is fabricated or unsupported statements. Grounding the scribe in the patient graph and requiring provenance for each statement is how we keep the draft faithful to what was actually recorded.
Will AI replace doctors?
No. Grounded clinical AI is decision support and documentation assistance: it surfaces cited evidence, drafts notes, and automates paperwork so clinicians decide faster with better information. Every consequential action stays under human review; the goal is to remove the busywork that burns clinicians out, not the clinician.
Explore the healthcare stack
Related healthcare capabilities.
Patient 360 & Record Linkage
Resolve the same patient across EHR, claims, lab, pharmacy, and device data into a canonical patient graph: the foundation for care coordination, risk stratification, and every downstream clinical AI.
Learn morePrior Authorization Automation
Model payer criteria as a graph, traverse the patient record for automated first pass adjudication, and file through Surescripts ePA: with explainable, evidence cited decisions both provider and payer can trust.
Learn moreHealthcare AI Compliance & Risk
HIPAA compliant, SOC 2 Type II, on prem/VPC deployment, PHI de identification, and full provenance: so your AI clears compliance instead of dying in it.
Learn moreReady to build clinical graphrag & decision support on grounded, compliant AI?
A 6 week pilot with one use case, fixed scope, and outcomes guaranteed in writing: hit the target or the pilot is free.