HealthEnclave AI
Hardware-enforced secure enclaves

Unlock AI for Clinical Research. Zero Data Exposure.

Our Confidential Computing platform processes patient data inside hardware-level secure enclaves — where even our own engineers cannot see it. HIPAA-compliant, GDPR-ready, and audit-verifiable by design.

SOC 2 Type II
HIPAA Aligned

Architected for Global Healthcare Compliance

HIPAA Compliant
GDPR Ready
SOC 2 Type II
HITRUST
ISO 27001

Trusted by leading CROs, biotech firms, and specialized clinics across 3 continents.

Traditional AI Has No Place in Clinical Data Environments

Standard cloud AI pipelines decrypt data in memory to process it. In sensitive clinical settings, this momentary exposure violates fundamental trust and regulatory bounds.

Data Breach Liability

Processing patient data through standard cloud APIs creates massive liability. Every unencrypted step in memory is a potential vector for costly clinical trial breaches.

Regulatory Exposure

HIPAA and GDPR violations strictly penalize inadequate data protection during computation. Fines and operational shutdowns halt critical research.

Failed De-identification

Legacy obfuscation methods fail against modern AI. True medical AI requires rich, context-heavy data — which makes traditional de-identification practically impossible without destroying utility.

Vendor Lock-in Risks

Relinquishing raw patient datasets to centralized API providers leads to profound vendor lock-in. Accessing and migrating your own proprietary models later becomes prohibitively expensive.

The AI Paradox in Healthcare

Standard cloud infrastructure promises encryption at-rest and in-transit. But during machine learning inference or model training, the memory space is decrypted and completely exposed to the hypervisor host. Every medical record processed is a vector for a silent breach.

The Solution

Confidential Computing: AI That Never Sees Your Data

Powered by hardware-enforced secure enclaves (Intel SGX and AMD SEV) we guarantee data privacy during computation. Data remains encrypted at-rest, in-transit, and in-use.

Medical researcher using secure terminal

End-to-End Encrypted

Status: Secure Enclave Active

1

Data Stays Encrypted

Patient data is encrypted strongly at the source using AES-256 before being transmitted securely over TLS 1.3.

2

Secure Enclave AI

AI models evaluate the encrypted data strictly inside isolated CPU enclaves. Even infrastructure admins cannot glimpse the memory.

3

Results Safely Delivered

Only cryptographically verifiable, aggregated insights are returned to your internal systems. Zero raw PII exposure.

Enterprise-Grade Capabilities Built for Healthcare's Highest Standards

A comprehensive, modular infrastructure meticulously architected to strip liability from the equation while pushing the boundaries of AI utility.

Zero-Knowledge AI Processing

AI insights derived without any team member (including ours) ever accessing raw data. Total elimination of standard cloud provider peering.

Hardware-Level Secure Enclaves

Intel SGX and AMD SEV-enforced isolation at the silicon level protects execution from the hypervisor down, securing data against OS-level compromise.

Federated Learning Capabilities

Train AI models across distributed, disparate clinical datasets without requiring the centralization of any raw patient records into a single honeypot.

Seamless EHR/EMR API Integration

Natively connect with Epic, Cerner, and modern HL7 FHIR-compliant architectures without demanding complete pipeline re-architecture.

On-Premise & Private Cloud Deployment

Retain uncompromising sovereignty. Implement directly within your own hardened infrastructure or dedicated strict-policy private clouds.

Audit Logs & Compliance Reporting

Generate immutable, timestamped computational and attestation logs instantly verifiable by external regulators and your own internal compliance officers.

Built for the Most Privacy-Sensitive Work in Medicine

Translating conceptual cryptographic assurances into tangible clinical accelerations. Discover exactly how organizations leverage zero-exposure AI.

Clinical Trials Data Processing

The Problem

Siloed datasets across varying international jurisdictions make multi-site AI modeling a massive GDPR and HIPAA regulatory roadblock.

The Solution

Deploy predictive models without cross-border centralization. Algorithms learn exclusively within decentralized, certified secure enclaves.

The Outcome

Halve standard bureaucratic trial durations while remaining totally unexposed to privacy litigations.

Patient Risk Prediction

The Problem

Executing live predictive diagnostic inference directly on active EHR pipelines typically mandates cloud exposures counter to strict hospital policies.

The Solution

Run isolated inferences synchronously against hospital nodes. At no point do standard memory buffers decode the raw diagnostic history.

The Outcome

Unlocks life-saving real-time deterioration predictions on data that standard vendors legally cannot touch.

Medical Imaging Analysis

The Problem

Training complex diagnostic architectures requires massive repositories of multi-modal DICOM files that are nearly impossible to fully anonymize.

The Solution

Image tensors operate encrypted inside designated CPU isolations. De-identification is bypassed entirely via fundamental obscuration.

The Outcome

Significantly higher fidelity oncology and radiology modeling driven by uncompromised, high-resolution original scannings.

Genomics & Bioinformatics

The Problem

Whole-genome sequencing files harbor permanent identifying sequences, meaning standard cloud aggregation constitutes endless systemic risk.

The Solution

Strict cryptographic workflows process petabytes of DNA strings inside sovereign enclave partitions. Computations dissolve post-execution.

The Outcome

True collaborative genomic drug discovery minus the data exposure liability inherent to shared computing spaces.

From Source to Insight — Your Data Never Leaves the Enclave

A demonstrably secure pipeline mapping the exact cryptography lifecycle rendering standard data breaches mathematically impossible.

1

Encrypted at Source

Patient data is encrypted strongly at the clinic or CRO using your proprietary keys before it ever moves across the wire.

2

Enters the Enclave

Encrypted data is directly ingested into a hardware-enforced Confidential Computing environment isolated from the host OS.

3

AI Processes Encrypted Data

AI models execute within the impenetrable enclave — the data is never decrypted or mirrored in externally accessible memory.

4

Verified Output Delivered

Only logically validated, de-identified insights and updated model weights are returned. Zero PII exposure risk.

Attestation Ready

Security That Compliance Officers Can Verify.
Not Just Trust.

We replace assumptions with mathematical certainty. Our architecture removes the need to implicitly trust cloud providers, mapping directly to rigorous HIPAA security rules and stringent GDPR data minimization statutes.

Hardware-Enforced Isolation Guarantees

Cryptographic separation means code execution occurs in a black box. Memory is unreadable to root operating systems, hypervisors, and data center engineers.

Continuous Cryptographic Attestation

Before data enters the enclave, our API furnishes a signed cryptographic proof directly to your compliance tooling, validating the exact hash of the software running. You don't send data unless the hash matches your audit records.

Technical Implementation Checklist

  • AES-256 military-grade encryption at rest
  • TLS 1.3 protocol enforced for data in transit
  • Ephemeral hardware-level memory encryption
  • Zero standing privileges (ZSP) for all staff
  • Strict role-based access controls (RBAC)
  • Mandatory MFA across all integration layers
  • Automated enclave termination upon physical tampering
  • Comprehensive BAA availability for HIPAA execution
  • 15-minute SLA incident response protocols
  • Right-to-erasure GDPR support inherent to design

Built at the Intersection of AI Engineering and Medical Ethics

The gap between AI's potential and healthcare's rigid data sovereignty constraints is massive. AI models require infinite data; hospital compliance policies mandate zero exposure. This friction point is where we operate.

Our mission is unequivocal: eliminate the data breach liability inherent to standard medical AI computation, thereby accelerating global biotech breakthroughs and clinical trials without ever compromising patient privacy.

Dr. Evelyn Hayes

Dr. Evelyn Hayes

Chief Medical Compliance Officer

Former HHS auditor and architect of GDPR health alignment protocols.

Marcus Thorne, PhD

Marcus Thorne, PhD

Chief AI Scientist

Pioneer in operationalizing federated learning across international medical boards.

Sarah Lin

Sarah Lin

Head of Security Engineering

15 years specialized in hardware cryptography and Intel SGX enclave structuring.

Answers to the Questions Your Compliance Team Will Ask

Clear, authoritative responses detailing exactly how our architecture satisfies uncompromising InfoSec demands.

Data is processed within hardware-enforced secure enclaves (Intel SGX / AMD SEV). Memory encryption guarantees that code and data remain opaque — even to root or hypervisor administrators.
In the event of physical or logical tapering, the secure enclave automatically terminates its process and destroys cryptographic keys in memory, preventing any access to decrypted state.
Our API connects directly via HL7 and FHIR standards. The data is encrypted locally at your source before transiting to our environment.
Yes. We provide cryptographic attestation reports proving the integrity of the enclave and the exact code binaries running inside.
Using Federated Learning, AI models train on-premise without raw data centralization. Alternatively, for cloud processing, data strictly leaves encrypted and only decrypts within the verifiable secure enclave.
AES-256 for data at rest, TLS 1.3 for data in transit, and hardware-enforced ephemeral memory encryption for data in use.
You can deploy seamlessly within completely sovereign on-premise networks or leverage our dedicated private cloud environments.
Since input data is never persisted outside isolated ephemeral memory and models preserve zero raw references, full lifecycle data minimization and instantaneous logical erasure are strictly maintained.
Yes. We welcome third-party audits and continuously perform independent penetration testing, validating our claims mathematically and practically.
Models train directly at the data nodes (clinics or hospitals). Only aggregated model weight updates — securely encrypted — are collected to refine the global AI, omitting individual records entirely.
With isolated architectures and instant termination triggers, zero-exposure guarantees apply. In abnormal termination events, response protocols trigger sub-15 minute alert SLAs.
Yes. We are completely prepared to sign a BAA for all clinical and enterprise entities required under HIPAA regulations.

Begin Your Secure Evaluation

We respect your data privacy. No sensitive data, PII, or PHI is required to initiate a technical architecture consultation.

End-to-End Encrypted Communication

Compliance & CISO Inquiry

ciso@healthenclave.ai

Direct Architecture Line

+1 (800) 555-0199

Headquarters

100 Secure Compute Way
Bldg 4, Enterprise Enclave
Cambridge, MA 02142