HIPAA-compliant, clinically grounded
I design and build production-grade healthcare RAG pipelines and clinical decision support chatbots grounded in your EHR systems, medical guidelines, and clinical notes—with zero PHI exposure, sub-100ms hybrid search, and deterministic safety guardrails.
Zero model training on patient data, BAA signed before any data access
Plain answer
A healthcare RAG (Retrieval-Augmented Generation) chatbot is an AI system that combines medical-grade language models with a secure, real-time knowledge retrieval engine. It extracts relevant context from EHR records, clinical guidelines, radiology reports, and drug formularies before generating an answer. By grounding every response in verifiable medical sources, it eliminates hallucinations, maintains strict HIPAA compliance, and provides doctors and patients with evidence-backed answers.
What I build
Custom, HIPAA-compliant retrieval pipelines and conversational AI assistants built specifically for medical systems.
Physician-facing assistants that retrieve and cross-reference institutional protocols, PubMed literature, and UpToDate guidelines in seconds.
24/7 patient-facing symptom intake chatbots that collect histories, match with clinical triage protocols, and route emergency cases immediately.
Multi-document synthesis across longitudinal patient records, lab histories, and doctor notes using HL7/FHIR compliant retrieval pipelines.
Real-time drug-to-drug interaction checkers and insurance formulary lookup tools that help prescribers select covered, compatible medications.
Rigorous evaluations for clinical accuracy, PHI leak vulnerabilities, prompt injection resistance, and hallucination boundary enforcement.
Try the clinical simulator widget above, or book a discovery session to scope your exact EHR integration.
Talk to an AI engineerDirect access vs agency
| Factor | Independent Healthcare AI Engineer (me) | Generalist AI Outsourcing Agency |
|---|---|---|
| Clinical & PHI expertise | Direct specialization in HIPAA Safe Harbor, FHIR, and clinical RAG | Generalist developers rotated across unrelated commercial verticals |
| Security & BAA accountability | Direct engineer signing BAA; zero third-party subcontractor exposure | Complex subcontractor chains increasing data breach liability |
| Deployment speed | Functional clinical POC in 2 to 3 weeks; production in 6 to 8 weeks | 3 to 6 months weighed down by account managers and discovery layers |
| Cost structure | Transparent milestone pricing without agency overhead markups | High monthly retainer overhead with billable hours for project managers |
Direct access guarantees higher compliance rigor
In healthcare, a misconfigured vector chunk or unmasked PHI field can result in severe HIPAA violations. Working directly with the engineer writing the ingestion and retrieval code gives your clinical leadership complete architectural clarity and unbroken communication.
Industry context
Proven architectures tailored to hospitals, digital health platforms, and medical research institutes.
Instant clinician lookup for ICU protocols, infection control guidelines, and post-op care steps without leaving the electronic chart.
Automating intake questionnaires, extracting structured medical history, and pre-populating doctor consultation summaries.
How it gets built
Clinical boundaries
Safety-first engineering in healthcare AI
A RAG chatbot is designed for clinical decision support, information retrieval, and patient navigation. It must never be deployed as an autonomous, unsupervised diagnostic authority for acute life-threatening emergencies. Any system offering medical guidance must enforce human-in-the-loop validation and unambiguous clinician oversight.
Investment
| Engagement type | What's included |
|---|---|
| HIPAA RAG Proof-of-Concept Free | De-identified retrieval pipeline on sample EHR/guidelines, safety eval report |
| Production Clinical RAG System | Full pipeline, FHIR integration, PHI scrubber, guardrails, VPC deployment |
| Healthcare AI Safety Audit | Red-teaming for hallucination, prompt injection, and PHI exposure risks |
| Hourly Medical AI Consulting | Architecture review, HIPAA compliance planning, retrieval strategy |
Delivered projects include AI clinical feedback categorization and automated medical literature synthesis. Full case studies at shreyans.tech/ai-case-studies.
FAQ
