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---
title: "User Profiles"
sidebarTitle: "User Profiles"
description: "Automatically maintained context about your users"
icon: "circle-user"
---
User profiles are **automatically maintained collections of facts about your users** that Supermemory builds from all their interactions. Think of it as a persistent "about me" document that's always up-to-date.
<CardGroup cols={2}>
<Card title="Instant Context" icon="bolt">
No search needed — comprehensive user info always ready
</Card>
<Card title="Auto-Updated" icon="rotate">
Profiles update as users interact with your system
</Card>
</CardGroup>
## Why Profiles?
Traditional memory systems rely entirely on search:
| Problem | Search Only | With Profiles |
|---------|------------|---------------|
| Context retrieval | 3-5 queries | 1 call |
| Response time | 200-500ms | 50-100ms |
| Basic user info | Requires specific queries | Always available |
**Search is too narrow**: When you search for "project updates", you miss that the user prefers bullet points, works in PST, and uses specific terminology.
**Profiles provide the foundation**: Instead of searching for basic context, profiles give your LLM a complete picture of who the user is.
---
## Static vs Dynamic
Profiles separate two types of information:
### Static Profile
Long-term, stable facts:
- "Sarah is a senior software engineer at TechCorp"
- "Sarah specializes in distributed systems"
- "Sarah prefers technical docs over video tutorials"
### Dynamic Profile
Recent context and temporary states:
- "Sarah is migrating the payment service to microservices"
- "Sarah is preparing for a conference talk next month"
- "Sarah is debugging a memory leak in auth service"
---
## How It Works
Profiles are built automatically through ingestion:
1. **Ingest content** — Users [add documents](/add-memories), chat, or any content
2. **Extract facts** — AI analyzes content for facts about the user
3. **Update profile** — System adds, updates, or removes facts
4. **Always current** — Profiles reflect the latest information
<Note>
You don't manually manage profiles — they build themselves as users interact. Start by [adding content](/add-memories) to see profiles in action.
</Note>
---
## Profiles + Search
Profiles don't replace search — they complement it:
- **Profile** = broad foundation (who the user is, preferences, background)
- **Search** = specific details (exact memories matching a query)
### Example
User asks: **"Can you help me debug this?"**
**Without profiles**: LLM has no context about expertise, projects, or preferences.
**With profiles**: LLM knows:
- Senior engineer (adjust technical level)
- Working on payment service (likely context)
- Prefers CLI tools (tool suggestions)
- Recent memory leak issues (possible connection)
---
## Use Cases
### Personalized AI Assistants
Profiles provide: expertise level, communication preferences, tools used, current projects.
```typescript
const systemPrompt = `You are assisting ${userName}.
Background: ${profile.static.join('\n')}
Current focus: ${profile.dynamic.join('\n')}
Adjust responses to their expertise and preferences.`;
```
### Customer Support
Profiles provide: product usage, previous issues, tech proficiency.
- No more "let me look up your account"
- Agents immediately understand context
- AI support references past interactions naturally
### Educational Platforms
Profiles provide: learning style, completed courses, strengths/weaknesses.
### Development Tools
Profiles provide: preferred languages, coding style, current project context.
---
## Next Steps
<CardGroup cols={2}>
<Card title="User Profiles API" icon="code" href="/user-profiles">
Fetch and use profiles via the API
</Card>
<Card title="Graph Memory" icon="network" href="/concepts/graph-memory">
How the underlying knowledge graph works
</Card>
<Card title="AI SDK Integration" icon="triangle" href="/integrations/ai-sdk">
Automatic profile injection with AI SDK
</Card>
<Card title="Add Memories" icon="plus" href="/add-memories">
Build profiles by adding content
</Card>
</CardGroup>
|