AI Memory for Personal Assistants

Build AI assistants that truly know their users. Remember preferences, habits, and context across every conversation.

The challenge

Every day is day one

Personal assistants forget everything between sessions. Users re-explain preferences, projects, and context every time.

No personalization

Without memory, the assistant gives generic responses that don't reflect the user's unique needs and style.

Can't learn habits

The assistant can't recognize patterns in the user's behavior — daily routines, recurring tasks, or preferred workflows.

No relationship building

AI companions feel shallow because they don't accumulate shared experiences or inside references.

How Mengram solves it

Deep personalization

Semantic memory stores preferences, interests, and personal details. The AI knows the user inside and out.

Shared history

Episodic memory remembers conversations, decisions, and events. The AI references past interactions naturally.

Learned routines

Procedural memory captures daily workflows, recurring tasks, and preferred processes that evolve over time.

Cognitive Profile

One API call generates a system prompt with the user's full context — making every LLM instantly personalized.

Quick implementation

from mengram import Mengram

m = Mengram(api_key="mg-...")

# Morning check-in — AI remembers everything
profile = m.profile(user_id="alice")
# "Alice is a product manager at Acme Corp. She prefers morning standup
#  summaries with bullet points. She's working on the Q1 launch...
#  Yesterday she reviewed the design specs and had feedback on the nav..."

# After each conversation, memory grows
m.add("Alice asked me to remind her about the design review on Friday. 
      "She also mentioned she prefers Figma links over screenshots.",
      user_id="alice")

# Next session: the AI remembers the reminder and preference
memories = m.search("design review", user_id="alice")

Results

100%

Context retention

∞

Session continuity

3 types

Memory depth

Build personal assistant agents with memory

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