T
Chennai, India
Technical Lead
Full-stack engineer leading the clinical platform build. Hospital-grade architecture, encounter flow, and infrastructure reliability.
LIET turns doctor-patient conversations into structured clinical notes and longitudinal patient memory — with optional suggestions you can review or ignore. Less time on paperwork. More time with the patient. The doctor is always in control.
Watch what the tool sees as the doctor speaks: live capture, gentle nudges on what hasn't been asked, and patterns surfaced for the doctor's review as they emerge. Shown here: a Tamil–English consultation, among the hardest LIET handles — the same flow runs in French, German, and English.
Available now
In development for European primary care
Luxembourgish support is on our roadmap.
LIET began with Indian primary care and is expanding to European markets. European-market features — GDPR consent, EU data residency, and regional drug databases — are in active development.
The doctor's workflow doesn't change. Speak naturally. The system organizes everything.
Consultation happens naturally. Real-time transcription captures every symptom, pertinent negative, examination finding, and medication — organized as it's spoken.
Positive history separated from negative history. Exam findings extracted. Brand names of medications captured accurately. Findings worth a second look are surfaced for the doctor's review. Investigation options listed. All in seconds.
Editable clinical document. Prescription editor. Physician-requested reference tools — clinical evidence, referral templates, investigation checklists. WhatsApp delivery to patient. Everything auditable. The physician confirms every output.
A 45-year-old woman. An 8-minute consultation in a regional Indian language. Here is what LIET surfaced for the doctor's review.
Illustrative example. A representative scenario built to demonstrate how LIET organizes a complex consultation — not a record of a real patient.
Surfaced frothy urine + new-onset hypertension (148/96) + bilateral edema together for the doctor's consideration. In a pain-first consultation, these threads are easy to miss.
Organized the findings against published SLICC 2012 criteria, for the doctor to weigh. Grouped suggested investigations by system — renal first (UPCR, microscopy, creatinine), then immunological (ANA, dsDNA, complement). Noted ANA methodology (IIF, HEp-2 substrate). The doctor decides what to order.
4 speech-to-text accuracy errors identified (drug name variants, family history formatting). The organized findings matched the reviewing physician's own interpretation.
What the product does today, and what comes next. We tell it straight.
Why documentation is the entry point — and why the data layer compounds quietly.
Across primary care — in Europe and in India — the same thing happens every day: the consultation happens, the note gets typed later from memory, and the detail is lost. The pattern across visits, the finding buried in a multilingual conversation — it disappears.
India alone generates 2.5 billion outpatient consultations a year, almost none of it searchable. In Europe, regulators are now mandating structured digital records — Luxembourg's CNS requires structured submission from GPs — yet the underlying capture problem is unsolved. LIET captures it at the source, in the doctor's own words, in any supported language.
Doctors need their notes done faster — that's the immediate value. But every note generated and reviewed by a physician creates something that doesn't exist elsewhere in primary care, in any market: searchable, longitudinal clinical data in the doctor's own corrected words. The documentation tool is useful on day one. The data layer it builds becomes valuable over time.
Each consultation adds to a growing knowledge substrate — physician-reviewed, multi-language clinical records with corrections, confirmations, and patterns across visits. The longer the system runs in a hospital, the harder it becomes to replicate what it has learned.
Every consultation generates searchable, analyzable clinical data — from any supported language.
Chief complaint, HPI, examination, diagnosis, investigations, advice — all organized fields.
Surfaces findings worth a second look — renal, cardiac, and neurological — for the doctor's review.
Separates pertinent positive symptoms from pertinent negatives — important for complete and defensible clinical documentation.
Every visit is captured as structured data linked to the patient, building the foundation for cross-visit memory (in development).
Proven first in Indian primary care — among the most linguistically complex outpatient settings in the world — and expanding to European markets.
Native multilingual recognition with real-time translation — proven on India's regional languages, extending to French, German, and English for European primary care. Handles mixed-language doctor-patient conversations, regional drug-brand pronunciations, and medical terminology under real outpatient conditions.
Structured note generation and investigation support, surfacing patterns across the conversation for your consideration — built for demanding clinical practice. Evidence-based protocols. Regional drug-brand awareness — Indian brands today, European formularies in development. Endemic and local disease context.
Row-level security. Immutable audit logs. Patient consent and data governance. Role-based access. FHIR R4 export in development. Secure cloud hosting; regional data residency in development. Every interaction logged and auditable.
Each layer builds on the one below. The doctors using LIET today shape the platform that serves the wider clinical community tomorrow.
AI-assisted documentation with suggestions you can review or ignore. LIET captures what's said and organizes it. The doctor decides everything.
When a patient returns months later, LIET surfaces their previous medications, the earlier reasoning, the investigations ordered — without manual chart-pulling. Memory across visits, in the doctor's own corrected words.
Across consultations, LIET surfaces patterns worth a doctor's attention — recurring presentations, response to treatment over time, subtle changes in a patient's trajectory. Brought to the individual visit, only with explicit consent and full de-identification.
Privacy and physician control come first — at every step, and as the product grows.
Over time, with explicit consent and full de-identification, aggregated clinical patterns can support medical research that improves care for everyone. Patient privacy and physician control come first, always. No identifiable patient data is ever shared.
A small team building multilingual clinical documentation for primary care.
Full-stack engineer leading the clinical platform build. Hospital-grade architecture, encounter flow, and infrastructure reliability.
Trained internal medicine physician. Leads clinical validations, product accuracy, and hospital partnerships.
Vehicle dynamics engineer. Background in complex systems modeling applied to healthcare. Leads product strategy, regulatory affairs.