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Healthcare · MedAgent

Give clinicians their documentation time back

MedAgent is a multi-agent system for clinical documentation, triage support, and record work. It runs against your EHR via FHIR, drafts rather than decides, and is designed for PHI-safe workflows under a BAA — every clinical output goes to a clinician for review.

Engagement snapshot

Typical engagement
2-4 week assessment, then 12-20 weeks to a first production workflow
First deliverable
Scoped agent architecture and a written go/no-go recommendation
Integrates with
EHR (FHIR/HL7), LIS, PACS
Human in the loop
Clinicians review and sign off every clinical output; agents draft, never decide
Full engagement tiers

What MedAgent is

MedAgent is our healthcare agent system — a reference architecture we customize, build, and deploy inside your existing clinical systems. It is not an off-the-shelf product you buy: you own the deployment, and we run design, build, evaluation, and handover.

See how we deliver

Signals it ingests

  • EHR · FHIR
  • VITALS
  • LAB RESULTS
  • IMAGING
01Capabilities

What MedAgent Can Do

Purpose-built AI agent capabilities for healthcare.

01 / 06

Clinical Decision Support

Real-time evidence-based recommendations that assist clinicians in making faster, more accurate treatment decisions at the point of care.

MedAgent capability
02 / 06

Patient Outcome Prediction

Advanced predictive models that analyze patient data to forecast outcomes, enabling proactive intervention and personalized care plans.

MedAgent capability
03 / 06

Medical Documentation

Automated generation of clinical notes, discharge summaries, and referral letters from patient encounters, reducing administrative burden.

MedAgent capability
04 / 06

Diagnostic Assistance

AI-powered analysis of symptoms, lab results, and imaging data to suggest differential diagnoses and recommended next steps.

MedAgent capability
05 / 06

Drug Interaction Analysis

Comprehensive medication cross-referencing that flags potential interactions, contraindications, and dosage adjustments in real time.

MedAgent capability
06 / 06

Appointment Optimization

Intelligent scheduling that balances patient urgency, provider availability, and resource constraints to minimize wait times.

MedAgent capability
02Process

How MedAgent Works

A structured path from signal ingestion to measurable production impact in healthcare.

01

Data Integration

MedAgent connects to EHR, lab, and medical imaging systems to aggregate patient data in real time inside your environment, under the PHI handling controls agreed in a BAA.

PHASE 01 / 03

02

Agent Processing

Specialized AI agents analyze clinical data in parallel — evaluating symptoms, cross-referencing medical literature, and applying evidence-based protocols to generate actionable insights.

PHASE 02 / 03

03

Clinical Output

Results are delivered directly into the clinical workflow as prioritized recommendations, auto-generated documentation, and decision-support alerts for the care team.

PHASE 03 / 03

03Use Cases

Real-World Applications

See how MedAgent solves critical challenges in healthcare.

Application

Emergency Triage Automation

Challenge

Emergency departments face overwhelming patient volumes, leading to long wait times and inconsistent triage decisions.

Agent solution

MedAgent analyzes vitals, symptoms, and medical history in seconds to assign accurate triage levels and flag critical cases immediately.

Outcome

Fewer mis-triaged patients and more consistent, evidence-based triage scoring across shifts; published ED-triage models reach ~80–99% accuracy (AUROC >0.80), with every recommendation clinician-reviewed.

Application

Radiology Report Generation

Challenge

Radiologists spend hours writing detailed reports, creating bottlenecks in diagnosis and treatment planning.

Agent solution

AI agents pre-analyze imaging studies, highlight anomalies, and draft structured reports for radiologist review and approval.

Outcome

Faster report turnaround with more consistent structure; ambient and drafting assistants save clinicians on the order of ~30 minutes per day, with every draft radiologist-reviewed.

Application

Patient Risk Stratification

Challenge

Identifying high-risk patients across large populations is time-consuming and often reactive rather than proactive.

Agent solution

MedAgent continuously monitors patient data to calculate risk scores and trigger early intervention protocols automatically.

Outcome

Earlier, proactive identification of at-risk patients so care teams can intervene sooner; risk scores are advisory and clinician-reviewed rather than autonomous.

Application

Clinical Trial Matching

Challenge

Matching eligible patients to clinical trials is a manual, error-prone process that misses many potential candidates.

Agent solution

AI agents cross-reference patient profiles against trial criteria in real time, surfacing matches to both clinicians and research coordinators.

Outcome

More eligible candidates surfaced for review and fewer missed matches; final eligibility decisions remain with clinicians and research coordinators.

Recognize any of these in your operation? Send us the workflow, its monthly volume, and the systems it touches — we will tell you which parts an agent should own and which should stay human.

Request a strategy call
04Architecture

Multi-Agent Collaboration

How specialized agents coordinate inside MedAgent.

▸ AGENT TOPOLOGYMedAgent
Input signals04
EHR · FHIRVITALSLAB RESULTSIMAGING
MedAgent core04
PlannerRouterMemoryRetrieval
Specialist agents04
Intake AgentTriage AgentDiagnostic AgentDocumentation Agent

Inputs

4 industry signals

Orchestration

MedAgent core

Agents

4 specialists

01

Intake Agent

Collects and normalizes patient data from multiple sources

02

Triage Agent

Assesses urgency and prioritizes clinical attention

03

Diagnostic Agent

Analyzes symptoms and generates differential diagnoses

04

Documentation Agent

Produces clinical notes and structured reports

05Impact

Operational outcomes we target

Target ranges and today's baseline, both drawn from published research. Actual results depend on your data, systems, and scope.

▸ TARGET

Less time on clinical documentation

30%

Source · Ambient-scribe randomized trials, UW Health and UCLA, 2024-25 (~30 min/clinician/day)

▸ TARGET

Clinicians reporting higher satisfaction after an ambient documentation rollout

82%

Source · Permanente ambient-AI deployment, 7,260 physicians

Where the baseline sits today

Published figures describing the current state of the industry — not results VelocityMind has delivered.

▸ BASELINE

Of physician time is spent on EHR and desk work today

49%

Source · Sinsky et al. / AMA

▸ BASELINE

Of US health spending is administrative today

25%

Source · McKinsey

07Get Started

Talk to us about MedAgent

Bring one workflow you want fixed. In 30 minutes we will tell you whether an agent system is the right answer for it — and roughly what it would take.

No commitment · We reply within one business day

▸ WHAT HAPPENS NEXT

01Initial response
Within one business day
02Strategy call
30-45 minutes, no commitment
03Roadmap draft
2-5 business days after the call