User Memory
Let your AI remember facts about users across conversations for personalized experiences.

User Memory enables your AI to remember important facts about users across conversations. Instead of starting fresh every time, your AI can recall preferences, past interactions, and relevant details.
What Is User Memory?
User Memory automatically extracts and stores durable facts from conversations:
| Memory Type | Examples |
|---|---|
| Fact | ”User’s company is Acme Corp”, “Works as a CTO” |
| Preference | ”Likes concise answers”, “Prefers email over phone” |
| Instruction | ”Always reply in Spanish”, “Don’t use bullet points” |
| Context | ”Evaluating the enterprise plan”, “Migrating off a legacy CRM” |
Each memory is also stored in one of two layers: Fact (durable, kept indefinitely) or Episodic (decaying, for things that matter for a while).
How It Works
User: "I'm the CTO at Acme Corp and we're evaluating your enterprise plan"
↓
[AI replies]
↓
[Memory extraction runs in the background]
↓
Memories stored:
- Role: CTO
- Company: Acme Corp
- Interest: Enterprise plan
↓
[Next conversation]
↓
AI: "Welcome back! Last time we discussed enterprise pricing for Acme Corp..."Enabling User Memory
Memory is on by default for new apps. To review or change it:
In your app’s builder, open Brain and then the Capabilities tab. Find the Memory card.
Toggle on Auto-extract memories. Your AI then learns preferences, facts, and context from conversations with each consumer.
Toggle on Recall memories in new conversations to carry saved facts about a consumer into their later conversations. Turn this off for assessment, intake, or eligibility flows, where each conversation must be judged only on what the person says in it. Turning both switches off turns memory off completely.
Toggle on Consumer memory access to let consumers view and delete their own memories from the chat menu. This is recommended for GDPR compliance.
To steer what the AI remembers or ignores, put that guidance in your system prompt (see “Memory in Your System Prompt” below).
Memory Categories
Fact
Personal facts about the user:
- Name, job, and location
- Company information
- Dietary restrictions, family, pets
Preference
Likes, dislikes, and style:
- Communication style (formal/casual)
- Response length preference
- Preferred formats (bullet points, paragraphs)
Instruction
How the user wants to be treated or how they want tasks done:
- “Always answer in Spanish”
- “Show the code before the explanation”
Context
Ongoing projects, goals, or situations:
- Problems they’re trying to solve
- Products they’re evaluating
- Deadlines they mentioned
Viewing Stored Memories
Go to Insights > Memory in the builder and select a consumer to see:
- All memories for that consumer
- When each memory was created
Filter the list by memory type (Preference, Fact, Instruction, Context, Experiential) or by layer (Episodic or Fact).
Managing Memories
Deleting Memories
Remove memories that are:
- Incorrect
- Outdated
- No longer relevant
Click the delete icon on a memory and confirm.
Clearing All Memories for a Consumer
For compliance or cleanup, select the consumer in Insights > Memory and click Clear all.
Best Practices
What to Remember
Do remember:
- Professional context (company, role, industry)
- Stated preferences
- Key topics discussed
- Problems they’re solving
Don’t remember:
- Sensitive personal information
- Temporary states (“having a bad day”)
- Information they asked you to forget
- Confidential business data without consent
Privacy Considerations
Always inform users that your AI has memory capabilities. Consider adding to your system prompt:
“I can remember relevant details from our conversations to provide better assistance. Let me know if you’d prefer I not remember something.”
Memory in Your System Prompt
Help your AI use memories effectively:
You have access to memories about this user from past conversations.
Use these to:
- Personalize greetings and responses
- Avoid asking questions they've already answered
- Reference their specific context
Don't:
- Mention that you "remember" things in a creepy way
- Assume memories are 100% accurate
- Reference memories if they seem outdatedHow Memory Extraction Works
Memory extraction happens automatically, in the background, after each AI reply:
- Turn completes: The AI finishes a reply (stopped or aborted replies are skipped)
- AI analysis: A Claude Haiku model reads the exchange for memorable facts
- Structured extraction: Facts are given a type (fact, preference, instruction, context) and a layer (durable fact or decaying episodic)
- Storage: Memories are stored against the consumer
Extraction is skipped for apps with Zero Data Retention turned on.
Use Cases
Customer Support
Remember:
- Product version they’re using
- Past issues they’ve reported
- Preferred contact method
- Technical expertise level
Sales Conversations
Remember:
- Company size and industry
- Budget discussions
- Decision timeline
- Stakeholders involved
Personal Assistants
Remember:
- Work schedule preferences
- Project names and contexts
- Communication preferences
- Recurring tasks
Educational Apps
Remember:
- Learning progress
- Topics mastered
- Areas needing work
- Preferred learning style
Troubleshooting
Memories Not Being Extracted
- Verify Auto-extract memories is on in the Memory card
- Check that Zero Data Retention is off for the app
- Allow a few moments after a reply for extraction to finish
- Verify the user is identified (not anonymous)
Incorrect Memories
- Delete incorrect memories
- Add guidance to your system prompt about what to remember and what to ignore
Too Many Memories
- Add system prompt guidance to prioritize durable facts
- Periodically clean up outdated memories
Limitations
Current limitations to be aware of:
- Extraction delay: Memories from a reply are written in the background, so they may not be usable in the very next message
- Anonymous users: Memories need an identified consumer
- Token limits: Very long conversations may be truncated for extraction
Using with MCP
You can access user memories programmatically using the Chipp MCP Server.
Available Tools
| Tool | Description |
|---|---|
get_user_memories | Retrieve memories stored for a specific consumer (app_id, consumer_id, optional type filter and limit) |
Example Prompts
"Show me the memories my support bot has for consumer 8f2c..."
"What facts has my app learned about this user?"
"List only the instruction memories for this consumer"Workflow: Reviewing User Insights
You: Show me the memories my sales bot has for john@acme.com
AI: [Looks up the consumer, then calls get_user_memories]
Found 6 memories:
- fact: CTO at Acme Corp, 500+ employees
- context: Evaluating the enterprise plan, budget approved
- preference: Prefers short, direct answers
...MCP server access requires a Builder plan or higher. See the MCP Setup Guide to get started.
Individual vs. group memory. User Memory stores facts about a single user — preferences, past interactions, and extracted insights. Circles complement this with shared group memory: a persistent context space that multiple users and AI agents read and write together. Use both for rich, personalized, and collaborative AI experiences.