All case studies

AI & Automation

Hospital management with AI-assisted triage

1,900 beds across six hospitals on a single HMS, with an intake agent that routes patients before they reach a desk.

Client

Northgate Care · Nashik

Industry

Healthcare

Timeline

16 weeks, phased per hospital

Team

8 (PM, 3 backend, 2 frontend, ML engineer, QA)

Northgate Care · Nashik — Hospital management with AI-assisted triage

Overview

Six hospitals, three different systems, and one unit still running on paper registers. A patient treated in Nashik whose file sat in Ozar effectively arrived as a stranger. The queue formed twice — once to register, once to find out which department they needed. And the insurance desk was rejecting its own work: a fifth of claims came back over missing paperwork, not medical grounds.

The challenge

  • Records did not travel with the patient between group hospitals.
  • 34 minutes on average from walking in to sitting in front of a doctor, during morning peak.
  • 21% of insurance claims rejected, almost all of it documentation, not clinical.
  • Bed occupancy was known once a day, in the morning report.

How we approached it

01

One identity per patient, with consent

A single MRN across the group, access granted on patient consent, and every read written to an audit log. We ran this past their legal and medical superintendents before building it, because trust here is the product.

02

Triage that starts on WhatsApp, at home

Patients describe the problem in Marathi, Hindi or English before leaving the house. The agent asks follow-ups, suggests a department and books a slot. It never diagnoses — anything clinical goes to a doctor, and it says so plainly.

03

Claims assembled by the system, not chased by a clerk

Discharge cannot complete until the checklist for that insurer is satisfied, and the packet builds itself in the insurer's own format. The claims team went from assembling files to reviewing them.

04

A live board instead of a phone hunt

Beds, OT slots and staff availability update as they change, so an admitting doctor stops making four calls to find a bed.

What we built

Unified patient record across six hospitals
Multilingual WhatsApp intake and triage agent
OPD, IPD, OT and pharmacy modules
Insurance pre-auth and claims packaging
Live bed and OT occupancy board
Role-based access with clinical audit trails

Technology stack

Frontend

  • Next.js
  • React
  • Tailwind CSS

Backend

  • Node.js
  • PostgreSQL
  • Queue workers

AI

  • LLM triage agent
  • WhatsApp Business API

The results

18 min

saved per admission

21% → 6%

claim rejection rate

62%

of intakes started on WhatsApp

6

hospitals on one platform

"I was against the WhatsApp agent for the first month. What changed my mind is that it hands over to a human the moment anything sounds clinical. Our front desk is no longer the bottleneck."
Dr. Anita KulkarniGroup Medical Superintendent, Northgate Care