Use Cases · Assistants
AI Memory for Personal Assistants
Personal assistant agents rely on long-term user memory — preferences, routines, contacts and past requests — to feel personal across weeks and months of use.
Assistant memory
Memory types
What personal assistants should remember
- Preferences — dietary restrictions, communication channel, timezone (semantic + user memory)
- Schedule patterns — “usually free after 5pm” (episodic → semantic promotion)
- Relationships — spouse name, manager, key contacts (semantic)
- Ongoing goals — “training for marathon in October” (episodic)
- Communication style — brief vs detailed, formal vs casual (user memory)
Privacy
Privacy and trust
Consent, transparency and a forget API — personal memory requires higher trust than generic chatbots.
- Disclose what is remembered and why
- Let users view and delete memories on request
- Scope all storage by
user_id - Filter sensitive data (health, financial) at extraction
- Support GDPR erasure with delete-all-memories API
Frameworks
Framework fit for personal assistants
- Engram — Weaviate-native per-user memory for personal AI-native apps; hybrid search, scoped collections
- Mem0 — fastest per-user personalization POC (LOCOMO J 66.9)
- Letta — long assistant threads with core/archival paging (MemGPT DMR 93.4%)
- Zep — when assistant facts evolve over time (temporal graph)
FAQ
Frequently asked questions
Best memory framework for personal assistants?
Engram for Weaviate-native personal apps; Mem0 for fastest per-user POC (LOCOMO J 66.9); Letta for long multi-week threads with paging. See best AI memory tools.
Does Mem0 work for assistant personalization?
Yes — both Engram and Mem0 extract and retrieve per-user facts automatically. Engram fits Weaviate-native stacks; Mem0 is framework-agnostic.
Does Claude have built-in assistant memory?
Claude's context window covers the current session. Durable cross-session memory requires external tools — Engram, Mem0 or custom vector stores.
Local-only memory for personal assistants?
Self-host Weaviate+Engram, Mem0 OSS, or Redis/pgvector DIY for full data residency. Managed APIs trade control for speed.
Cross-device memory sync for assistants?
Centralize memory in a cloud store keyed by user_id — Engram, Mem0 or Zep. Devices read/write the same collection.
Is Engram good for personal assistants?
Yes — scoped per-user collections, hybrid search and managed write pipeline on Weaviate. GA June 2026. See Engram explained.
GDPR forget for personal assistant memory?
Implement delete-all-memories per user_id. Engram, Mem0 and Zep all support per-user deletion. See forgetting and eviction.