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🏥 Healthcare🏗️ 4 Tech Levels🚀 Production-Grade🔒 HIPAA Compliant

Patient Intake AI

See 4 architectures solve real problems: MCP → RAG → Multi-Tool → Multi-Agent

April 18, 2025
demointeractivepatient-intakehealthcaremulti-agent
🤖Demo 1 of 4

Advanced Multi-Agent System

BOFU: Production LangGraph with Router → Specialized Healthcare Agents → Orchestration

1. Select Analysis Scenario

New patient with chronic conditions, incomplete insurance info, requiring multi-agent collaboration
Competitors: Patient: John Doe, 67, Type 2 Diabetes + Hypertension, Insurance: Medicare (incomplete policy number), Medications: 5 current (2 missing dosages)

2. Monday's Prompt

This positioning analysis prompt from Monday's insight will be processed by Tuesday's agents in Wednesday's workflow.

3. Run Multi-Agent Workflow

You'll see 5 AI agents: Data Collector → Messaging Analyzer → Position Mapper → Strategy Advisor → Insight Generator
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🔌Demo 2 of 4

MCP Tool Use Pattern

TOFU: LLM calls healthcare tools via Model Context Protocol - see real tool execution

Automation Task

User provides intake form → LLM decides tool (extract_patient_demographics) → Executes → Returns structured data

Monitoring:Patient: Sarah Chen, 34, Female
ai-agent-terminal

Terminal ready. Run simulation to begin.

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🔍Demo 3 of 4

RAG-Based Patient Search

MOFU: Search 1000+ patient records with vector similarity

Search Query

"Find Similar Patient Cases"

Embed query → Search patient vectors → Retrieve top 5 similar cases → Generate comparative analysis

Document Sources:Patient A: 62yo male, chest pain, Type 2 DM, HTN, troponin elevatedPatient B: 55yo male, chest pain, Type 2 DM, HTN, normal troponinPatient C: 60yo male, chest pain, Type 2 DM, HTN, STEMI confirmedPatient D: 59yo male, chest pain, Type 2 DM, HTN, GERD diagnosedPatient E: 57yo male, chest pain, Type 2 DM, HTN, anxiety-related

RAG Vector Search Network

Embedding
Searching
Generating
Query
Vector
Documents
Result

Search Results

Run visualization to see results

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🛠️Demo 4 of 4

Multi-Tool Intake Orchestration

MOFU: Multiple healthcare tools working together automatically

ROI Analysis

Orchestrator calls: Intake Executor (extract data) → Validation Evaluator (check completeness) → Question Generator (ask follow-ups) → Guardrail (HIPAA check) → EHR Integrator (populate charts) - all in parallel per patient

Integrations:150 patients in daily queue105 simple intakes (auto-completed)45 complex intakes (follow-up questions generated)All charts auto-populated in Epic by 9am
Manual Process

Time to Complete

240 min

Cost per Analysis

$850

Data Points Analyzed

150

Accuracy Rate

73.0%

Reports per Day

2

Error Rate

18.0%

Ready for Production Patient Intake System?

We'll build your custom HIPAA-compliant system: MCP tools (TOFU) → RAG search (MOFU) → Multi-tool (MOFU) → Multi-agent (BOFU). From demos to deployment in 8-12 weeks. Includes: HL7/FHIR integration, Epic/Cerner connectors, HIPAA BAA, SOC 2 compliance, clinical validation.

Book Architecture ReviewStart with MCP Tools (TOFU)
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