01
Clinical note & discharge summary drafting
Voice in the consultation room → structured SOAP note → discharge summary, with section detection and ICD-10 / SNOMED code suggestions. Doctor reviews, signs, files — never leaves the LAN.
Industry · Healthcare & Hospitals
Clinical intelligence
that never leaves the hospital network.
Patient data is the most sensitive data an institution holds. Marxen builds AI for Indian hospitals that processes it entirely on-premise — clinical workflow support, voice and document AI, and a sovereign HMS underneath it all.
§ 01The problem
PHI cannot ride a foreign API. Period.
Protected health information — patient names, diagnoses, prescriptions, lab values — is the highest-sensitivity data class an Indian hospital holds. The DPDP Act treats health data as 'sensitive personal data', and most hospital boards have already decided informally that it must not leave the institution. Cloud AI cannot honour that constraint cleanly.
Marxen builds AI that runs entirely inside the hospital network. Voice goes from the consultation room to an on-prem ASR. Documents go from the registration desk into on-prem retrieval. Models live on a GPU server the hospital owns. Nothing crosses the perimeter.
§ 02Use cases
Where AI earns its place. In healthcare.
Ten concrete workflows where Marxen has deployed — or can deploy — sovereign AI in healthcare institutions.
- 02
Voice-first symptom collection
Tamil, Hindi, and Telugu voice intake at OPD registration. The patient describes the problem in their language; the system structures it for the doctor before the encounter begins.
- 03
Formulary-grounded drug interaction checks
Prescriptions checked against the hospital's own formulary, lab values, allergies, and history — not a generic public dataset that doesn't know Indian brands.
- 04
Medical coding assistance for billing
Encounter notes mapped to ICD-10, CPT, and TPA-specific codes. Coders review proposals instead of writing from scratch. Cleaner claims, faster reimbursement.
- 05
Radiology report drafting
Modality-aware drafts for X-ray, CT, and MRI reports — the radiologist edits and signs instead of dictating from blank.
- 06
Insurance pre-authorisation automation
TPA pre-auth packets assembled from the EMR — patient history, line of treatment, line items, supporting reports — and reviewed against payer rules before submission.
- 07
Patient history search over the EMR
Clinicians ask the chart in plain language: 'show me her HbA1c trend over the last two years, and any antibiotics in the last six months.' Answers cite the source notes.
- 08
Discharge follow-up & adherence
Vernacular SMS / IVR follow-up — medication adherence, post-op symptoms, appointment reminders — routed back to the care team only on a flag.
- 09
Lab value anomaly narration
Lab pulls flag clinically significant deltas — not just out-of-range but trending. The narration is human-readable, the data stays in the LIS.
- 10
Front-desk multilingual assistance
Wayfinding, scheme eligibility (Ayushman Bharat, state schemes), and FAQ — handled in the patient's language at the registration counter, by AI that lives on the hospital's own server.
§ 03The Marxen approach
What we deploy. Inside the hospital LAN.
Naadhi HMS
The full hospital management system — OPD, IPD, OT, lab, pharmacy, radiology, billing — with AI woven through every workflow, not bolted on.
On-prem inference
GPU server inside the hospital, OpenAI-compatible API, no calls to external endpoints. Air-gap supported.
Indic ASR & TTS
Speech models tuned for clinical Tamil, Hindi, Telugu — including code-switching with English drug names.
Document retrieval
Formularies, SOPs, discharge templates, and patient charts indexed and grounded — answers cite the source.
§ 04Compliance
DPDP, NDHM, NABH — by architecture.
Every Marxen healthcare deployment is built to pass the audits Indian hospitals actually face. DPDP-aligned data handling, NDHM/ABDM-ready FHIR interfaces where required, and NABH-compatible audit trails on every workflow. Aadhaar masked by default, reveal-on-consent only inside a permission-gated drawer.
We do not store PHI outside the hospital. We do not call foreign APIs. We do not train shared models on your data.
- DPDP Act
- ABDM · NDHM
- NABH
- FHIR R4
- Aadhaar masking
§ 05Anchor product
Already built for healthcare. Already in production.
Start a healthcare conversation
Tell us your use case. We'll tell you honestly whether sovereign AI is the right move.
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