Healthcare AI

    AI that knows your patients

    Healthcare AI fails when it doesn't know patient history. Allergies, past reactions, communication preferences, family involvement — this context saves lives. Memory makes it accessible.

    Patient Dashboard
    HIPAA Compliant
    Patient Overview
    Maria Rodriguez
    Age 67Type 2 Diabetes
    Last visit: 3 days ago
    Medications: Metformin, Lisinopril
    Patient Memory

    Struggles with medication adherence • Prefers morning reminders • Daughter helps with appointments • Had adverse reaction to Glipizide in 2019

    AI Insights

    The cost of forgotten context

    In healthcare, context isn't just convenient — it's critical. A patient's history of adverse drug reactions, their communication preferences, their family support system — this information directly impacts care quality and safety.

    But most healthcare AI systems treat each interaction as isolated:

    Medication safety gaps

    Maria had an adverse reaction to Glipizide in 2019. Without memory, an AI assistant might suggest it again. With memory, it knows to recommend alternatives and flag the history.

    Adherence patterns missed

    A patient consistently misses afternoon medications but takes morning ones. Without this pattern, reminders are generic. With memory, the AI adjusts timing and involves family members who've helped before.

    Communication preferences ignored

    James responds well to data and numbers. Sarah prefers simple explanations. Without memory, every patient gets the same generic communication style.

    Patient memory that's compliant and secure

    MemoryStack provides HIPAA-compliant memory storage with end-to-end encryption, complete audit trails, and patient-scoped isolation. Your AI gets the context it needs while maintaining the security healthcare requires.

    1

    Complete patient context

    Store medication history, allergies, adverse reactions, communication preferences, family involvement, and care patterns. Retrieve relevant context instantly when needed.

    2

    Proactive care insights

    Identify patterns across patient history. Detect adherence issues before they become problems. Suggest interventions based on what's worked before for this specific patient.

    3

    Care team coordination

    When a patient sees a new provider, all relevant context is available. No more "tell me your history again" — the AI knows and can brief the provider appropriately.

    Built for healthcare compliance

    HIPAA Compliant

    End-to-end encryption, BAA available, SOC 2 Type II certified infrastructure. Your patient data is protected at every layer.

    Complete Audit Trail

    Every access is logged with provider ID, timestamp, and access reason. Full compliance reporting for audits and investigations.

    Patient Isolation

    Each patient's data is cryptographically isolated. No possibility of cross-patient data leakage, even in multi-tenant deployments.

    Data Residency

    Choose where your data lives. US, EU, or specific regions. Meet local healthcare data regulations wherever you operate.

    Simple API, serious security

    The same simple API you'd use for any application, with healthcare-grade security built in. No complex configuration — compliance is the default.

    AES-256 encryption at rest and in transit
    Automatic audit logging for every access
    Patient-scoped data isolation
    BAA available for HIPAA compliance
    healthcare.py
    from memorystack import MemoryStack
    
    # HIPAA-compliant configuration
    client = MemoryStack(
        api_key="your-api-key",
        encryption="AES-256",
        audit_logging=True
    )
    
    async def patient_assistant(patient_id: str, query: str):
        # Get patient history with full audit trail
        history = await client.search(
            query=query,
            user_id=patient_id,  # Patient-scoped isolation
            limit=20
        )
        
        # History includes:
        # - Medication history and reactions
        # - Previous conditions and treatments
        # - Communication preferences
        # - Family/caregiver information
        # - Appointment patterns
        
        recommendation = await generate_care_recommendation(
            query=query,
            patient_history=history
        )
        
        # Every access is logged for compliance
        await client.add(
            content=f"Query: {query}\nRecommendation: {recommendation}",
            user_id=patient_id,
            metadata={
                "type": "care_note",
                "provider_id": current_provider_id,
                "access_reason": "patient_care"
            }
        )
        
        return recommendation

    Build healthcare AI that remembers

    Start with 1,000 free memories. HIPAA compliance included.