Healthcare AI that remembers patient context, medical history, and care preferences across every interaction.
Patients describe their history, medications, and symptoms every time they interact with the AI assistant.
AI health assistants don't track conversations over time — missing patterns in symptoms, mood, or behavior.
Without patient context, AI gives generic recommendations instead of personalized guidance based on history.
Healthcare data must stay within controlled environments. Cloud-only solutions don't meet compliance needs.
Semantic memory stores patient preferences, conditions, and care notes. Always available for personalized interactions.
Episodic memory tracks symptom reports, mood changes, and care interactions over time — surfacing patterns.
Procedural memory captures proven care pathways and follow-up procedures that improve with each patient interaction.
Deploy Mengram on your own infrastructure. All memory stays within your data boundary. MIT licensed.
from mengram import Mengram
# Self-hosted for data sovereignty
m = Mengram(base_url="https://your-mengram.internal.com")
def patient_interaction(patient_id: str, message: str):
# Full patient context in one call
profile = m.profile(user_id=patient_id)
# "Patient is managing Type 2 diabetes. Prefers morning check-ins.
# Last reported A1C: 7.2%. Current medications: metformin.
# Last visit: discussed increasing exercise routine."
# Search for relevant history
history = m.search(message, user_id=patient_id)
# After interaction, store for continuity
m.add(f"Patient reported: {message}", user_id=patient_id)Context retention
Data sovereignty
Ready architecture
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