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AI Medical Intake

Structured intake, before the consultation begins.

Collect patient complaints and relevant history through an adaptive conversation, then hand clinicians a structured, API-ready intake instead of free text.

Get API AccessAPI reference
POST /v1/intake/analyzeSynthetic example
response.json
{
  "session_id": "demo_session_1l7eha",
  "status": "needs_clinician_review",
  "language": "en",
  "structured_intake": {
    "chief_complaint": "Headache and nausea",
    "qualifiers": [
      "persistent"
    ],
    "duration": "not yet specified",
    "reported_symptoms": [
      "headache",
      "nausea"
    ],
    "patient_age": 34,
    "follow_up_questions": [
      "When did the headache begin?",
      "Have you vomited, and if so, how many times?",
      "Have you experienced any additional symptoms?"
    ]
  },
  "next_action": "ask_follow_up",
  "disclaimer": "Decision-support draft for clinician review. Not a diagnosis."
}

Responsible use

Intake summarizes what the patient reported. It does not interpret findings or establish a diagnosis; clinicians review every intake.

Capabilities

Conversational intake that ends in structured data.

Status labels show what is in development today and what is planned.

  • Multilingual patient conversations

    In development

    Conversations in English, Russian, Kazakh, and Uzbek.

  • Symptom collection

    In development

    Captures onset, duration, severity, and context.

  • Adaptive follow-up questions

    In development

    Next questions depend on what the patient has said.

  • Structured medical intake

    In development

    Normalized fields instead of unstructured notes.

  • API-ready JSON output

    In development

    Typed responses your system can store and route.

  • Embedded patient workflows

    Planned

    Drop into portals, apps, and booking flows you own.

Workflow

How it fits your product

Key output fields
chief_complaintonset & durationreported_symptomsfollow_up_questions
Typical host systems
Patient portalsTelemedicine appsBooking flows
  1. 1

    Patient describes the problem

    In your app, in their language, in their own words.

  2. 2

    Evergate asks follow-ups

    Adaptive questions fill gaps in the clinical picture.

  3. 3

    Structured intake returned

    JSON delivered to your system for clinician review.

Playground

Try the request and response

All examples on this site use synthetic data. No real patients, recordings, or inference requests are involved.

Demo mode · syntheticProposed
POST/v1/intake/analyze
Examples

Valid JSON

ResponseAwaiting request

No response yet.

Run the request to inspect the structured JSON response.

Responses are generated in your browser by deterministic demo rules over your request. They show the response schema — they are not results of a real inference request. Do not enter real patient data.

Compose with other modules

AI Medical Intake shares authentication, sessions and webhooks with every Evergate module.

Your healthcare software deserves intelligence.

Integrate medical AI into the systems you already use.

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Evergate — Medical Intelligence Infrastructure