01 · Listens
Listens
Ambient AI captures the natural doctor-patient conversation with 97% accuracy in real Indian clinical environments - noisy, multilingual, and unforgiving of error.
India · AI-native clinical platform
The neural layer of modern healthcare.
AI-native clinical documentation and full-stack HMIS, built from the ground up so clinicians can return to medicine.
97% voice accuracy·Discharge summaries in under 10 seconds·Trusted by hospitals across India.
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The signal journey
You talk. Axone writes - and the signal never stops moving.
A single clinical sentence travels through five stages in one breath: captured, understood, structured, validated, and filed into the record.
01
Voice
Clinician speaks
02
AI Model
Specialty-routed
03
Structured Note
FHIR-native
04
Validated
NABH · SNOMED
05
EHR
Audit-trailed
97%
voice-to-text accuracy
70%
documentation time saved
10s
per discharge summary
The platform
India's first AI-native clinical documentation and full-stack hospital management platform.
Built from the ground up with artificial intelligence at the foundation, not bolted onto legacy systems. A platform that gives clinicians their time back.
02 · Understands
Understands
Fine-tuned clinical language models built specifically for Indian medicine structure raw observation into casesheets, differential diagnoses, and discharge summaries in real time.
03 · Delivers
Delivers
Complete, compliant clinical documentation across 27+ forms and charts. NABH and ABDM ready, FHIR R4 native, generated in under 10 seconds.
The problem
The hidden cost of modern medicine is time.
Talk to any practising clinician in India. The first complaint is rarely about patients. It’s about the screens between them and patients.
- 01
A doctor spends 2 hours of every shift on paperwork.
- 02
A discharge summary takes 35 minutes to write.
- 03
Nurses fill 27+ forms per patient per day.
- 04
This is time stolen from patients.
- →
We give it back.
Interactive demo
Rough dictation in. Ready-to-sign summary out.
Pick a case to see the kind of rough clinical speech a doctor gives, then watch Axone structure it into a clean, formatted discharge summary - the same layout that lands in your hospital’s records.
Choose a case
Ready
Bed 12 · MedicineClinician input
rough dictationHey Axone, discharge summary for bed 12. 62-year-old male, admitted with fever, cough, breathlessness for 4 days. Known diabetic and hypertensive. Chest X-ray showed right lower zone consolidation. WBC was high, CRP high. Started on IV antibiotics, nebulisation, insulin sliding scale, oxygen initially. Improved over 4 days, now afebrile, maintaining saturation on room air. Discharge with oral antibiotics, inhaler, diabetes and BP meds, follow-up after 7 days.
Discharge Summary
draft · unsigned
Press “Run demo” to turn the medicine case dictation into a formatted discharge summary.
Measured outcomes
The numbers our customers see.
Pulled from production deployments in hospitals across India. Verified against ground-truth chart audits.
0%
Voice-to-text accuracy
Real clinical settings
0 sec
Discharge summary
Down from 35 minutes
0 sec
Admission note
Down from 10 minutes
0+
Forms automated
Doctor and nurse workflows
THE DATA LAYER
Every hospital sits on years of clinical truth. Most of it is unreadable to machines.
Records, vitals, labs, imaging, prescriptions - wound around each patient like a double helix. Axone unwinds it, structures it, and gives it back to the people who can act on it.
- 01Ingest every encounter - voice, text, paper, scanned.
- 02Resolve to FHIR R4 resources with SNOMED + ICD-10 codes.
- 03Surface what matters at the moment of care.
Two products. One AI foundation.
Start with the Documentation Platform on top of your existing systems. Or deploy the full AI-native operating system. Or combine both. The choice is yours, and it can change over time.
Pick one. Pick both. Pick a single module. The platform is built to flex around your hospital, not the other way around.
What gets automated
Twelve clinical workflows, automated by default.
These aren’t templates a clinician fills in. They’re generated from the actual conversation, written in your hospital’s house style, and ready for sign-off. Twenty-seven plus nursing forms are generated the same way.
Discharge summary
35 min → under 10 sec
Admission note
10 min → under 10 sec
OPD encounter note
Generated mid-conversation
Vitals + nursing chart
12 forms auto-populated
Prescription + medication chart
Drug-drug + allergy checks inline
Lab + investigation order
Coded to LOINC + ICD-10
Consent + pre-op forms
Signed digitally, NABH-compliant
Operative note
Voice during the procedure
Birth + paediatric chart
Growth charts auto-tracked
Radiology report
Structured + DICOM-linked
Handover summary
Shift change, generated in seconds
Adverse event / red flags
Surfaced from chart in real time
From the first OPD note to the final discharge summary - one collaborative platform, continuous care.
OPD consultations. Admission notes. Doctor’s orders. Vitals. Progress notes. OT notes. Shift handovers. Discharge summaries. Forms and charts. Every clinical artifact across the entire patient journey - captured, structured, and connected. Doctors and nurses work on the same platform. The patient’s clinical story flows continuously, from the first consultation to the day they walk out.
- OPD Consultation
- Admission Notes
- Doctor's Orders
- Vitalscontinuous
- Progress Notesper shift
- OT Notesif applicable
- Nursing Formscontinuous
- Shift Handoversper shift
- Discharge Summary
One platform for doctors and nurses
No more clinical notes living in one system and nursing forms in another. Same login, same patient view, same intelligence layer.
Continuity of care, by default
What happens at admission informs the discharge. What nurses chart informs the doctor's next round. The patient's clinical story is one story, not nine fragments.
Collaborative, not parallel
Doctors annotate nursing notes. Nurses flag concerns to doctors in-line. The platform is built for handover, not for handoff.
How it works
From conversation to compliant chart, in three steps.
01
We listen
Ambient AI captures the clinical conversation as it happens - ward rounds, OPD encounters, dictation - without interrupting the clinician.
02
We understand
Fine-tuned 7B–13B clinical LLMs structure the observation into SOAP notes, ICD-10 codes, FHIR R4 resources and discharge summaries.
03
We deliver
Compliant documentation lands in the EHR, ready for sign-off. Hospital data stays inside hospital infrastructure.
VOICE INPUT
Ambient capture in noisy wards
SPECIALTY MODEL
LoRA adapter routes to one of 45+ specialties
STRUCTURED NOTE
Casesheet, DD, summary - generated
EHR DELIVERY
Signed, compliant, hospital-resident
LATENCY
From conversation to chart in the time it takes to walk to the next bed.
Voice → specialty-routed model → structured note → EHR. The clinical signal travels end-to-end before the synapse fades.
- 38msp50 inter-token latency on a single L4 GPU.
- 71msp95 latency under real ward acoustic load.
- 0msHospital data leaving the building.
THE NEURAL INTEGRATION PROTOCOL
Axone layers on top of your existing software.
No rip-and-replace. No 6-month integration project. The Documentation Platform connects to your current HMIS, draws patient context in real time, and writes documentation back to your existing chart. Your IT team keeps the systems they trust. Your clinical team gets the AI they need.
Integration is accelerated by our proprietary Neural Integration Protocol - an AI layer that learns your existing HMIS’s schemas, APIs, and data conventions automatically. Deployments that traditionally take months go live in weeks.
Weeksto deployment
1module to start
0rip-and-replace
HIS
Billing
Lab
Pharmacy
NEURAL INTEGRATION PROTOCOL
Axone Documentation Platform
Why now
Three forces just converged for the first time. We built Axone to be the first thing through that gap.
Hospitals in India and Southeast Asia have been told to wait for an EHR renaissance for fifteen years. The renaissance never came because the economics didn’t work, the compliance rails didn’t exist, and the AI couldn’t hold a clinical conversation.
In 2026 those three blockers fell, in the same eighteen-month window. We built Axone to be the first thing through that gap.
1.4B
people
India will absorb the largest healthcare load on earth this decade. The system needs to ten-x productivity, not capacity.
70%
of clinician burnout
is documentation-driven. Ambient AI is the first lever that actually moves the needle.
< $0.40
per inference
is what 13B clinical LLMs cost in 2026 on a quantized L4. Two years ago this required a 4-GPU cluster.
ABDM
rails matured
India’s digital health stack is consent-driven, FHIR-native, and interoperable by law - finally.
Built for Indian healthcare
Compliance is the moat. So we built it in from day one.
Hospitals can’t bolt regulation onto a system later. Axone is FHIR R4 native, SNOMED-coded, ICD-10 ready, NABH-aligned and ABDM-integrated from inception.
Hospital data stays inside hospital infrastructure. Inference can run on-prem, in private cloud, or air-gapped.
NABH
Quality + Patient safety
ABDM
India’s digital health stack
FHIR R4
Interoperability native
SNOMED CT
Clinical terminology
ICD-10
Coding standard
ISO 27001
Information security
Engineering behind it
Boring infrastructure, on purpose.
We resisted the urge to build a research lab. Axone is an inference platform that ships into hospitals - quantized models, predictable latency, deterministic deployments.
Unlike legacy EHRs whose enterprise deployments routinely run into multi-crore annual contracts, Axone delivers a more advanced AI-native platform at a fraction of the cost - without bolting AI onto an old core.
- 01$ axone-serve start \
- 02 --engine vLLM --model axone-clinical-13b-q4
- 03vLLM 0.6.x · TensorRT-LLM optional
- 04GPTQ / AWQ 4-bit quantization
- 05NVIDIA T4 / L4 / A100 supported
- 06Token latency: p50 38ms p95 71ms
Quantized 13B clinical LLMs run on a single L4 - acceptable economics for Indian hospitals.
Our early partners
Trusted by India's leading hospitals.
Deployed across multi-specialty hospitals in South India. Real wards, real language, real workflows - not pilots in a sandbox.
Aster CMI Hospital
Bengaluru · Multi-specialty tertiary care
Vikram Aura Hospitals
Bengaluru · Multi-specialty
“For the first time in my career, I finished rounds with the chart already done. The cognitive break that gave me was worth the rest of the system on its own.”
“Our nurses got their lunch break back. That sentence sounded small until I lived it.”
A note from the founder
We are building Axone because we were the doctors typing at 9pm.
I trained at JIPMER. By the end of every ward day, my colleagues and I would still be in front of a screen for two more hours - writing notes for patients we had already cared for. When ambient AI became real, it was obvious what to do with it: give clinicians their evenings back, then their consults back, then the bandwidth to think about hard cases again.
Axone is the smallest possible bet on that idea - AI-native clinical documentation and a full hospital OS, priced per patient, deployed where hospitals already are. No multi-year transformation programmes, no demos that don’t survive contact with a real ward. If you run a hospital and you want your clinicians back, we should talk.
Dr. Arnab Chatterjee
Co-Founder & CEO · Axone Health · JIPMER alumnus
FAQ
Questions hospital leaders ask us in week one.
If something here isn’t obvious, ask us in the demo - we’d rather over-answer than under-deliver.
Those products bolt AI onto a legacy EHR core. Axone is AI-native - the model, the data layer, and the UI are designed to assume ambient AI from the first row of the database. Practically, this means we automate dozens of clinical workflows out of the box, not three.
Talk to us
Give your clinicians their day back.
We do 20-minute focused walkthroughs for hospital leadership, and longer conversations with investors and partners exploring the category.
- · We respond to demo requests within one business day.
- · We share deployment models and pricing on the first call.
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