AI for healthtech — grounded, safe, and clinician-friendly.
Healthcare AI must reduce clinician burden without inventing facts. I help healthtech teams build grounded, rigorously evaluated AI — from EMR copilots to clinical knowledge assistants — drawing on having architected a physiotherapy EMR OS and an AI clinical-intelligence platform.
Grounded clinical RAG — answers from verified sources, not guesses
In healthcare, a hallucination is a patient-safety issue
Clinicians won't trust AI that's occasionally wrong, and regulators won't accept it. Medical AI has to be grounded in real evidence and continuously measured.
Hallucinations in a medical domain
Generic LLMs confidently produce unsafe clinical answers without grounding and evaluation.
Clinician overload
Documentation and admin steal time from patient care — but tools must save effort, not add it.
Privacy & trust
Patient data demands careful handling, access control and auditability.
Where AI helps in healthtech
Speech-to-Notes & SOAP automation
LLMs auto-draft clinical notes from consultations, saving clinicians significant time per day.
Grounded clinical knowledge assistants
RAG over verified medical and practitioner knowledge bases for context-aware, faithful answers.
Semantic patient-record retrieval
Instantly surface relevant history and prior notes to speed up decision-making across sessions.
Patient engagement & adherence
AI-guided exercise coaching, reminders and multilingual guidance between visits.
Triage & intake support
Structured, assistive intake that routes and summarises for the care team — with humans in the loop.
Medical-grade evaluation
RAGAs + LangSmith pipelines that track faithfulness and drive down hallucinations continuously.
Proof, not promises
- ✓Architected Bharat's-first-style physiotherapy EMR OS across web, iOS and Android
- ✓Engineered Speech-to-Notes SOAP automation saving ~45 minutes per clinician per day
- ✓Built semantic patient-record retrieval with vector search (Pinecone)
- ✓Created a RAGAs evaluation framework that measurably reduced medical hallucinations
- ✓Designed multi-tenant, role-based clinical platforms (Admin / Clinician / Patient)
Domain experience
I've built real clinical software — EMR, AI notes, and a RAG-based clinical-intelligence platform — so I understand both the engineering and the safety bar healthcare AI must clear.
Questions, answered
How do you stop medical AI from hallucinating?+
Through grounding (RAG over verified sources), strict evaluation with RAGAs for faithfulness and precision, LangSmith tracing, and human-in-the-loop review for anything clinical. Quality is measured daily, not assumed.
Can AI really reduce clinician workload?+
Yes — for example, AI Speech-to-Notes can auto-draft SOAP notes and save roughly 45 minutes per clinician per day, letting them focus on patients instead of paperwork.
What about patient data privacy?+
I design with multi-tenant isolation, role-based access, and careful data handling, so AI features respect privacy and access rules from the architecture up.
Do you build clinical AI or just advise?+
Both. I provide advisory engagements and hands-on builds, and can act as a fractional CTO for healthtech startups.
Ready to put AI to work in your business?
Book a consultation and leave with a concrete, high-ROI next step.
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