Your AI agents
shouldn't forget.

Liebed gives AI agents persistent, intelligent memory. Store what matters, understand context, and retrieve the right information at the right moment.

Built for agents, copilots, assistants, and autonomous systems.

User
AI Agent
Liebed Memory
Extract
Remember
Connect
Update
Retrieve
Relevant Context
AI Agent Response

Built for the next generation of AI applications

AI Agents AI Assistants Copilots Autonomous Systems Multi-Agent Systems

AI has intelligence.
It doesn't have memory.

Today's AI agents are trapped inside context windows. Every conversation risks losing important information. Developers are forced to stitch together vector databases, RAG pipelines, chat history, summaries, and custom memory systems.

Liebed makes memory a native capability.

Without Liebed

Conversation
Context Window
Forget
Start Over

With Liebed

Conversation
Liebed Understands
Important Memories Persist
Relevant Context Retrieved

More than a vector database.

Intelligent Memory Extraction

Liebed automatically identifies meaningful information instead of storing everything blindly.

Long-Term Persistence

Memories survive beyond conversations, sessions, and context windows.

Contextual Recall

Retrieve the information that matters for the current task, not just keyword matches.

T-1
Now

Temporal Intelligence

Understand when something happened, whether it is still true, and how information has changed.

×

Contradiction Resolution

When new information conflicts with old memories, Liebed detects and intelligently updates the memory state.

Memory Graphs

Connect people, events, preferences, concepts, and experiences into an evolving semantic memory graph.

One memory layer. Every agent.

01

Ingest

Your application sends conversations, events, documents, or observations to Liebed.

02

Understand

Liebed extracts entities, facts, relationships, importance, and temporal information.

03

Remember

Important information is transformed into structured, evolving long-term memory.

04

Recall

Your agent asks a question. Liebed retrieves and composes the most relevant context.

Memory through a
simple API.

Integrate Liebed into any agent architecture with just a few lines of code. No need to manage vector databases, embed models, or write complex chunking logic.

Explore the API
await liebed.remember({
  user_id: "user_123",
  content: "Sarah is building an AI startup called Liebed.",
  metadata: {
    source: "conversation"
  }
});

Memory isn't a list.
It's a living system.

Interact with the memory graph. Liebed builds evolving semantic networks that connect concepts, people, and time.

Hover to explore connections

Built for memory, not storage.

Capability Traditional Database Vector Database Liebed
Store data
Semantic search ×
Long-term memory ×
Temporal awareness × ×
Contradiction handling × ×
Automatic memory extraction × ×
Relationship understanding × ×
Memory importance scoring × ×
Context-aware retrieval ×
Memory evolution × ×

Memory for every kind of intelligence.

AI Assistants

Give assistants persistent knowledge about users and conversations. No more starting from scratch every session.

Autonomous Agents

Allow agents to learn from previous actions, outcomes, and failures to continuously improve their decision making.

Enterprise Copilots

Maintain organizational context across thousands of interactions, projects, and internal documents.

Multi-Agent Systems

Give multiple agents access to a shared, evolving memory state to coordinate complex tasks seamlessly.

Give your AI a memory.

Stop rebuilding context from scratch. Build agents that remember, learn, and understand over time.

Developer-first. API-native. Built for scale.