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Healthcare

AI for healthcare that works at the bedside, not in a slide deck.

We embed engineers inside hospitals, diagnostics chains, and health-tech platforms for 4 weeks walk every ward, shadow every OPD, map every HL7/FHIR feed. Then we ship HIPAA-compliant, DPDPA-aligned AI every month. 62% reduction in claim-denial rework is not a slide it is what a multi-speciality chain measured in 90 days.

fewer claim-denial reworks

faster OPD discharge summaries

radiology throughput on CT/MRI triage

Root Causes

Why most "AI for healthcare" pilots die in the corridor

The model was trained on US data

Indian ICD coding practices, payer behaviour, and diagnostic patterns differ. A US-trained denial model calls 40% of Indian claims "anomalous". Trust collapses in week one.

Clinicians were never consulted

The workflow was designed by a product manager in an office park. The senior doctor on the ward finds the UI adds 3 clicks and abandons it by day 4.

Data is locked inside the HIS vendor

Closed EMRs, proprietary HL7 wrappers, undocumented APIs. Integration eats 60% of project budget before a single model is trained.

Nobody owns consent and audit trails

DPDPA and HIPAA both require verifiable consent and access logs. Most pilots skip this until the hospital compliance officer kills the project in user-acceptance testing.

Impact Dashboard

Every metric is a problem we solved.

Real numbers from live healthcare deployments.

Claim denials eat 2–4% of topline

0%
fewer denial reworks
Pre-Submission Claim Scrubber

Discharge summaries drown doctors

0%
0255075100
faster discharge summaries
Ambient Clinical Scribe

Prior-auth blocks the patient, not the fraud

0%faster prior-auth TAT
Prior-Auth Copilot

Patient no-shows waste premium slots

No-show rate before0%
After smart recall0%
no-show rate
No-Show Prediction
Reality Map

What your team actually says.

"I spend more time typing than examining."

Senior Consultant

"Our denial rate is 11%. I have no idea which payer, which coder, which doctor."

Revenue Cycle Head

"We have 3,000 unread CTs in the worklist. Something urgent is in there."

Head of Radiology

"22% of our premium slots are empty and we still have a 3-week waiting list."

OPD Manager

"Every integration with the HIS takes 6 months and a lawyer."

CIO

"Our NABH auditor flagged 14 missing consent records last quarter."

Quality & Compliance

Real Impact

Use cases that move the needle.

01

01Ambient AI Scribe for OPD & Wards

Voice-to-structured-note capture during consultations. Auto-drafts SOAP notes, discharge summaries, and prescriptions inside the EHR.

41% faster discharge summary turnaround
02

02Pre-Submission Claims Scrubbing

AI validates ICD-10/CPT codes, prior-auth status, and documentation against payer rules before the claim leaves the hospital.

62% fewer denial reworks
03

03Radiology Triage & Critical-Finding Alerts

Pre-read AI models re-rank CT/MRI worklists and page radiologists for suspected stroke, PE, and intracranial bleed.

20-minute turnaround on critical findings
04

04Prior-Authorisation Bot

Auto-drafts and submits prior-auth packets with clinical evidence attachments, tracks payer SLAs, and escalates delays.

55% reduction in prior-auth cycle time
05

05Patient No-Show & Revenue-Recovery Model

Per-slot no-show probability feeds smart recall, SMS/WhatsApp nudges, and overbooking rules for premium OPD.

22% → 11% no-show rate
06

06Discharge Summary Auto-Drafting

LLM ingests admission notes, progress notes, lab and imaging results to produce a HIPAA-compliant discharge summary draft.

30+ minutes saved per discharge
The 9AI Model

Four pillars. Translated for Healthcare.

01

An Engineer in Your OPD

Our Forward Deployed Engineer shadows consultants, sits in on MDT meetings, and walks through billing, coding, and discharge workflows. They speak HL7, know how NABH auditors think, and understand why the casualty medical officer writes notes the way they do.

02

Clinical-Grade R&D

Our Research Engineers run 2-week sprints on real de-identified data Indian ICD-coding patterns, regional payer behaviour, language mix in clinical notes so the model works in your hospital, not just on MIMIC-IV.

03

A Working Release Every 30 Days

Mid-month shadow deployment next to the doctor. End-of-month go-live in one department. Every release has a clinical sign-off, audit logs, and a rollback plan. No six-month "phase 1" that never reaches a patient.

04

We Own the Clinical & Financial Number

We don't bill hours. Every month you get a report: denial-rate delta, documentation time saved, critical-finding TAT, no-show-rate change. If the numbers aren't moving, you'll know and so will we.

The 4-Week Audit

What happens in the first 30 days.

1
Week 1

Workflow Walk & Data Inventory

Our engineer shadows OPD, IPD, radiology, and billing. Interviews consultants, nurses, coders, and the CFO. Maps every HL7/FHIR feed and every EHR module in use.

2
Week 2

Compliance & Integration Mapping

HIPAA, DPDPA, NABH requirements documented. Consent flows mapped. EHR/HIS integration surface documented, including vendor-locked blockers.

3
Week 3

AI Opportunity Scoring & Mockups

Each opportunity scored by clinical impact, ₹ impact, feasibility, and data readiness. Clinician-validated mockups built for the top 3 use cases.

4
Week 4

Strategy Deck & Clinical Roadmap

Prioritised 12-month roadmap, cost-benefit case, integration architecture, and change-management plan handed over. Yours to keep regardless of what comes next.

What you walk away with

End-to-end workflow SOPs across OPD, IPD, radiology, and billing
HIPAA / DPDPA / NABH compliance gap assessment
EHR/HIS integration architecture diagram
Clinician-validated mockups for top 3 AI use cases
12-month implementation roadmap with ROI model
Data readiness and consent-flow documentation
Compliance & Stack

We speak your regulatory language.

Regulations & Certifications

  • HIPAA — US Protected Health Information safeguards
  • DPDPA 2023 — Indian Digital Personal Data Protection Act
  • NABH — National Accreditation Board for Hospitals
  • MCI / NMC Guidelines — Clinical documentation standards
  • IRDAI Claim Rules — Health-insurance claim documentation

Data & Protocol Standards

  • HL7 v2 / v3
  • FHIR R4
  • DICOM (imaging)
  • ICD-10 / ICD-11
  • SNOMED CT
  • LOINC

Enterprise Systems We Integrate

  • Epic, Cerner, Meditech
  • Allscripts, athenahealth
  • Indian HIS Suvarna, Birlamedisoft, Insta, Hinai
  • PACS GE, Philips, Agfa
  • TPA / payer portals Paramount, MDIndia, HDFC Ergo
  • Tally / Oracle Financials for billing
FAQ

Questions we hear on the shop floor.

Start here

Book the 4-Week Healthcare Audit

HIPAA · DPDPA · NABH-aware. FHIR-native. EHR-integrated.

The first step is always a conversation.

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9AI Logo

Embedded AI Growth Office.

We turn your company into an AI Native company.

Company

AboutCase StudiesContactBlogIndustries

Resources

Media & NewsCareersCrunchbase
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