Letta

Agents with stateful memory (formerly MemGPT)

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Overview

Letta (formerly MemGPT) was built around one observation: most agents lose context the moment a session ends. Letta makes memory the first-class primitive: core memory, archival memory, conversation history, all persisted automatically.

This is what you want when the use case is "an AI that knows the user over months": long-running assistants, customer support bots that remember prior tickets, internal knowledge agents that learn the company.

The hosted Letta Cloud handles persistence and scaling; the open-source server is self-hostable for security-conscious deployments.

Key Features

Core Memory

Always-on context the agent edits over time

Archival Memory

Vector-backed long-term storage for retrieval

Persistent Identity

Agents that survive process restarts

Tool Use

Function calling with the standard schemas

Model Agnostic

Run on OpenAI, Anthropic, or local models

Open Source

Apache 2.0 with a hosted cloud option

Why We Recommend Letta

Stateful memory is the missing piece in most agent stacks. Letta gives it to you without rolling your own vector + summary pipeline.

Quick Info

Need help with Letta?

Our engineers work with Letta daily and can help you integrate it into your stack.

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