HealthcareSecurity & Data SovereigntyVPC / On-Premise

HIPAA-Compliant Patient Summaries

Automate clinical documentation by locally scrubbing Patient Health Information (PHI) before leveraging powerful external LLMs, ensuring strict HIPAA compliance and zero data leakage.

The Baseline

Problem

Doctors spend hours writing patient summaries but cannot use standard ChatGPT due to HIPAA restrictions. Exposing PHI to public AI models violates federal law, breaches patient trust, and carries massive financial penalties.

Solution

Privacy Shield acts as a local proxy, scrubbing all Patient Health Information (PHI) before routing the clinical notes to an external LLM, then re-attaching the identities locally upon return.

Result

Automates clinical documentation while guaranteeing 100% HIPAA compliance. Physicians reclaim hours of administrative time daily, and hospital IT maintains total data sovereignty and regulatory control.

Architecture Flow

1

Data Ingestion (Internal)

A physician completes a consultation and dictates or types raw clinical notes into the hospital's Electronic Health Record (EHR) system. The EHR securely pushes this raw text to the AVELIN API.

2

Local Scrubbing (Privacy Shield)

Before the data leaves the hospital's firewall, AVELIN's Privacy Shield intercepts the payload. Local edge models detect and strip all PHI (patient names, dates of birth, addresses, Medical Record Numbers) and replace them with secure, randomized tokens.

3

External Inference (Model Engine)

The completely anonymized clinical text is routed to a premium external LLM (e.g., OpenAI or Claude). The model processes the medical narrative, extracts diagnostic context, and generates a structured clinical summary.

4

Local Re-Assembly

The AVELIN platform receives the anonymized summary from the external provider, securely maps the tokens back to the original PHI locally, and pushes the final, fully identified summary directly back into the patient's EHR file.

Core Infrastructure

ComponentRole
Privacy ShieldExecutes localized Named Entity Recognition (NER) to detect, redact, and tokenize highly sensitive PHI at the edge before any internet transmission occurs.
Model EngineManages the API routing to external LLMs. Allows hospital IT to instantly swap between providers (e.g., OpenAI to Anthropic) based on performance or changing compliance rules.
Orchestration EngineManages the seamless bidirectional data flow between the hospital's legacy EHR system, the local scrubbing proxy, and the external AI models.

Technical Specifications

Encryption

AES-256 for data at rest; TLS 1.3 for data in transit

Compliance

Fully HIPAA, HITECH, and SOC2 Type II compliant architecture

Infrastructure

Deploys natively inside your existing AWS/Azure VPC or entirely on-premise on hospital servers

Build this architecture

Map this workflow to your internal data models. Deploy AVELIN AI to gain sovereign control over your enterprise intelligence.

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