Hospital-Specific AI Solution

No more generic chatbots —
Hospital-Specific AI

A hospital-specific AI configured from the hospital's own articles, blog, YouTube, and consultation data intakes patient inquiries 24/7 in 14 languages. The response flow is reviewed and run by the hospital — Kind Doctor provides the infrastructure.

Hospital Data

Articles
Blog
YouTube
Consults
PDF
Internal
Hospital LLMHospital-specific model

14-language response

English한국어日本語中文+11

Operates only on data the hospital reviews and approves

Why Hospital-Specific AI

What Generic Chatbots Can't Do

A dedicated AI built from each hospital's own data — preserving your hospital's brand and response authority

Generic Agency / Public AI

  • Generic responses that struggle with hospital brand and context
  • Per-hospital data and operating information stay siloed
  • Hospital-specific response policies are hard to apply
  • Inquiry history scattered across channels

Kind Doctor AI System

  • Hospital-exclusive LLM configured from the hospital's own data
  • 14-language inquiry intake and booking assist, 24/7
  • Inquiry → AI front-line guidance → hospital inbox → consultation handoff → booking confirmation assist
  • Response flow the hospital reviews and runs directly

Patient Response Operations Flow

1
Inquiry Intake
2
AI Front-line Guidance
3
Hospital Inbox
4
Consultation Handoff
5
Booking Confirmation Assist
6
Pre-visit Guidance

LINEUP 2 — IN-HOUSE OPERATIONS AI

Manuals that grow as questions accumulate.

A hospital-exclusive LLM for staff training, manual writing, and repetitive Q&A.

Manuals That Grow Themselves

When new staff ask, the manager answers — and that answer becomes part of the SOP automatically. After a year, hundreds of operational assets accumulate.

Onboarding 30 → 18 Days

No more 50% repeat-question burden on senior staff. Senior staff focus on real patient care; new hires reach autonomy faster.

No Response Variance

Identical answers regardless of seniority or location. Owner console visualizes this week's top questions and where bottlenecks are.

KNOWLEDGE LOOP

How the in-house manual grows

1

New staff asks

A junior staff posts a question into the in-house AI

2

Manager answers

The senior manager reviews and submits the canonical answer

3

SOP auto-filing

The Q&A is auto-classified into the SOP knowledge base

4

Knowledge grows

Manuals accumulate without anyone writing them from scratch

↻ Knowledge Loop

5-LAYER ISOLATION

Patient data and staff data are stored in completely separate vaults.

Only staff Q&A is accumulated — patient personal data is never used for training.

Layer 1

Public hospital content

Layer 2

Staff FAQ

Layer 3

In-house SOP knowledge

Layer 4

Staff inquiry logs

Layer 5

Patient personal data — isolated, never used for training

Isolated

Pricing: Custom by hospital size — Phase 0 pilot in progress

Inquire for Hospital
Glass Box Transparency

No more opaque response process, Glass Box Operations Log.

An operations log the hospital sees directly. Inquiry intake, AI front-line response, consultation handoff, booking confirmation — every response step is recorded on the hospital screen in real time.

1

Full Response Log

Every step from inquiry intake to final hospital confirmation is recorded

2

Live Response Status

Inbox, consultation handoff, and booking-assist progress are visible in real time

3

AI Front-line Response

AI handles repetitive inquiries and basic guidance; only flagged items reach hospital staff

Live Operations Log
Today
today
42
Inquiries
done
38
AI 1st response
in flight
12
Handoff
pending
7
Booking req.
pending
4
Deposit req.
pending
3
Awaiting hospital
Weekly Response Flow7 days