Skip to main content
User profiles are automatically maintained collections of facts about your users that Supermemory builds from all their interactions and content. Think of it as a persistent “about me” document that’s always up-to-date and instantly accessible.

Instant Context

No search queries needed - comprehensive user information is always ready

Auto-Updated

Profiles update automatically as users interact with your system

Two-Tier Structure

Static facts + dynamic context for perfect personalization

Zero Setup

Just ingest content normally - profiles build themselves

​
Why Profiles?

Traditional memory systems rely entirely on search, which has fundamental limitations:
ProblemWith Search OnlyWith Profiles
Context retrieval3-5 search queries1 profile call
Response time200-500ms50-100ms
ConsistencyVaries by search qualityAlways comprehensive
Basic user infoRequires specific queriesAlways available
Search is too narrow: When you search for “project updates”, you miss that the user prefers bullet points, works in PST timezone, and uses specific terminology. Profiles provide the foundation: Instead of repeatedly searching for basic context, profiles give your LLM a complete picture of who the user is.

​
Static vs Dynamic

Profiles intelligently separate two types of information:

​
Static Profile

Long-term, stable facts that rarely change:
  • “Sarah Chen is a senior software engineer at TechCorp”
  • “Sarah specializes in distributed systems and Kubernetes”
  • “Sarah has a PhD in Computer Science from MIT”
  • “Sarah prefers technical documentation over video tutorials”

​
Dynamic Profile

Recent context and temporary states:
  • “Sarah is currently migrating the payment service to microservices”
  • “Sarah recently started learning Rust for a side project”
  • “Sarah is preparing for a conference talk next month”
  • “Sarah is debugging a memory leak in the authentication service”

​
How It Works

Profiles are automatically built and maintained through Supermemory’s ingestion pipeline:
1

Content Ingestion

When users add documents, chat, or any content to Supermemory, it goes through the standard ingestion workflow.
2

Intelligence Extraction

AI analyzes the content to extract not just memories, but also facts about the user themselves.
3

Profile Operations

The system generates profile operations (add, update, or remove facts) based on the new information.
4

Automatic Updates

Profiles are updated in real-time, ensuring they always reflect the latest information.
You don’t need to manually manage profiles - they build themselves as users interact with your system.
Profiles don’t replace search - they complement it:
1

Profile provides foundation

The user’s profile gives your LLM comprehensive background context about who they are, what they know, and what they’re working on.
2

Search adds specificity

When you need specific information (like “error in deployment yesterday”), search finds those exact memories.
3

Combined for perfect context

Your LLM gets both the broad understanding from profiles AND the specific details from search.

​
Example

User asks: “Can you help me debug this?” Without profiles: The LLM has no context about the user’s expertise level, current projects, or debugging preferences. With profiles: The LLM knows:
  • The user is a senior engineer (adjust technical level)
  • They’re working on a payment service migration (likely context)
  • They prefer command-line tools over GUIs (tool suggestions)
  • They recently had issues with memory leaks (possible connection)

​
Next Steps

API Reference

Learn how to fetch and use profiles via the API

Code Examples

See complete integration examples

AI SDK Integration

Use the AI SDK for automatic profile injection

Use Cases

Common patterns and applications