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 |
|---|---|
| Saved Facts | "User's company is Acme Corp", "Prefers email over phone" |
| Preferences | "Likes concise answers", "Uses metric system" |
| User Insights | "Technical background", "Decision maker for purchases" |
| Topic Highlights | "Interested in enterprise pricing", "Asked about API limits" |
How It Works
User: "I'm the CTO at Acme Corp and we're evaluating your enterprise plan"
↓
[Conversation ends]
↓
[Memory extraction runs]
↓
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
Open Memory Settings
Go to your app's Build page and find Memory Settings in the sidebar.
Enable Memory Extraction
Toggle on Enable User Memory. This activates automatic memory extraction from conversations.
Configure Categories (Optional)
Choose which types of information to remember:
- Saved Facts: Concrete information (names, companies, roles)
- Preferences: How users like to interact
- Topic Highlights: Key discussion topics
- User Insights: Inferred characteristics
- Recent Queries: Common questions asked
Set Custom Instructions (Optional)
Add specific extraction guidance:
Focus on:
- Company size and industry
- Budget constraints mentioned
- Technical requirements discussed
- Decision timeline
Do NOT remember:
- Personal contact information
- Specific financial figures
- Confidential business details
Memory Categories
Saved Facts
Concrete, verifiable information:
- Names and roles
- Company information
- Product preferences
- Account details
Preferences
How users like to interact:
- Communication style (formal/casual)
- Response length preference
- Preferred formats (bullet points, paragraphs)
- Language preferences
Topic Highlights
Key subjects from conversations:
- Features they're interested in
- Problems they're trying to solve
- Questions they've asked
- Products they've discussed
User Insights
Inferred characteristics:
- Technical expertise level
- Decision-making authority
- Industry background
- Use case patterns
Viewing Stored Memories
Go to Chats > select a user > Memories to see:
- All memories for that user
- When each memory was created
- Which conversation it came from
- Confidence score
Managing Memories
Editing Memories
Click on any memory to edit or correct it:
- Update the content
- Change the category
- Adjust confidence score
Deleting Memories
Remove memories that are:
- Incorrect
- Outdated
- No longer relevant
Go to Memories > click the memory > Delete.
Bulk Management
For compliance or cleanup:
- Delete all memories for a user: User profile > Clear Memory
- Export memories: Download as CSV for review
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 outdated
How Memory Extraction Works
Memory extraction happens automatically after conversations:
- Conversation ends: User leaves or 10 minutes of inactivity
- Queued for processing: Conversation enters the memory queue
- AI analysis: GPT-4 analyzes the conversation for memorable facts
- Structured extraction: Facts are categorized and scored for confidence
- Storage: Memories are encrypted and stored with the user profile
Extraction Timing
| Trigger | When It Happens |
|---|---|
| Inactivity | 10 minutes without messages |
| User leaves | Explicit session end |
| Batch processing | Every 10 minutes for queued sessions |
Confidence Scores
Each memory has a confidence score (0-1):
- 0.9-1.0: Explicitly stated by user
- 0.7-0.9: Strongly implied
- 0.5-0.7: Reasonable inference
- Below 0.5: Uncertain, may need verification
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 memory is enabled in settings
- Check that conversations are ending properly
- Allow 10-15 minutes for extraction to process
- Verify the user is identified (not anonymous)
Incorrect Memories
- Review and edit incorrect memories
- Adjust custom extraction instructions
- Add negative examples to instructions
Too Many Memories
- Focus extraction on specific categories
- Add instructions to prioritize durable facts
- Periodically clean up outdated memories
Limitations
Current limitations to be aware of:
- Extraction delay: Memories aren't available instantly (10+ minute delay)
- No real-time recall: Current implementation extracts but doesn't automatically inject into prompts
- Token limits: Very long conversations may be truncated for extraction
We're actively improving the memory system. Future updates will include real-time memory recall and more sophisticated memory management.
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