--- title: "letta vs Memori" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/letta-ai-letta-vs-memorilabs-memori" tools: ["letta-ai-letta", "memorilabs-memori"] --- # letta vs Memori Neutral, constraint-first comparison with live GitHub stats. | | [letta](/tools/letta-ai-letta.md) | [Memori](/tools/memorilabs-memori.md) | | --- | --- | --- | | Tagline | Platform for stateful agents with advanced memory capabilities | Memory infrastructure for AI agents that captures actions and conversations into a structured, persistent state. | | Stars | 23,708 | 15,549 | | Forks | 2,510 | 2,784 | | Open issues | 49 | 21 | | Language | Python | Python | | Adopt for | Letta is a platform for building AI agents with advanced memory capabilities, supporting both local and cloud deployment, making it ideal for projects that require persistent learning and state management. | Memori is designed for enterprise users seeking seamless memory infrastructure that integrates with existing data architectures across multiple deployment environments. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Memori is licensed under the Apache License 2.0. | | Categories | LLM Frameworks, AI Agents | Model Training, AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [letta](/tools/letta-ai-letta.md) | [Memori](/tools/memorilabs-memori.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 4d | 22d | | Open issues (now) | 49 | 21 | | Security scan | 8 low (8 low) | No lockfile | | Full report | [trust report](/tools/letta-ai-letta/trust.md) | [trust report](/tools/memorilabs-memori/trust.md) | **Typed relationship:** letta _(alternative)_ Memori Both Letta and Memori provide memory infrastructure for AI agents, though they implement this functionality differently. ## Shared compatibility - **Node.js**: [letta](/tools/letta-ai-letta.md) - Node.js runtime; [Memori](/tools/memorilabs-memori.md) - Node.js runtime - **Python**: [letta](/tools/letta-ai-letta.md) - Python runtime; [Memori](/tools/memorilabs-memori.md) - Python runtime ## Decision facts: letta - **Pricing:** unknown - Details regarding pricing are not provided in the repository data. - **Requirements:** Installation requires Node.js version 22.19+; Dependencies include the Letta Code CLI tool installed globally via npm. - **Adopt for:** Letta is a platform for building AI agents with advanced memory capabilities, supporting both local and cloud deployment, making it ideal for projects that require persistent learning and state management. ## Decision facts: Memori - **Pricing:** unknown - Pricing details are not explicitly stated in the provided repository content. - **Requirements:** The tool requires set up of an API key for Memori and your LLM - **Adopt for:** Memori is designed for enterprise users seeking seamless memory infrastructure that integrates with existing data architectures across multiple deployment environments. - **License detail:** Memori is licensed under the Apache License 2.0. ## Choose when ### Choose letta if… - License: letta is Apache-2.0, Memori is Other. - Pricing: Details regarding pricing are not provided in the repository data.. - Requirements: Installation requires Node.js version 22.19+; Dependencies include the Letta Code CLI tool installed globally via npm.. - Both Letta and Memori provide memory infrastructure for AI agents, though they implement this functionality differently. - Tags unique to letta: llm, self-improvement, memory-system, development-platform. - Also covers LLM Frameworks. - Use Letta when you need a platform to develop AI agents that can learn and self-improve over time through their interactions. ### Choose Memori if… - License: Memori is Other, letta is Apache-2.0. - Pricing: Pricing details are not explicitly stated in the provided repository content.. - Requirements: The tool requires set up of an API key for Memori and your LLM. - Both Letta and Memori provide memory infrastructure for AI agents, though they implement this functionality differently. - Tags unique to Memori: stateful, memory-management, ai-memory, llm-agnostic. - Also covers Model Training. - When you need a system to turn agent execution and conversation into structured, persistent state without disrupting your current IT environment. ## When NOT to use letta - Avoid using Letta if your project strictly needs real-time data processing without statefulness; it focuses on agents with memory capabilities which adds to the complexity. - Do not use Letta if you are looking for a minimalistic solution since its advanced features and SDK might introduce unnecessary overhead. ## When NOT to use Memori - Avoid if you need a tool that natively extends beyond memory management to include features like autonomous agent navigation or extensive model training utilities, as Memori focuses specifically on AI ## Common questions ### What is the difference between letta and Memori? letta: Platform for stateful agents with advanced memory capabilities. Memori: Memory infrastructure for AI agents that captures actions and conversations into a structured, persistent state.. See the comparison table for live GitHub stats and shared categories. ### When should I choose letta over Memori? Choose letta over Memori when License: letta is Apache-2.0, Memori is Other; Pricing: Details regarding pricing are not provided in the repository data.; Requirements: Installation requires Node.js version 22.19+; Dependencies include the Letta Code CLI tool installed globally via npm.; Both Letta and Memori provide memory infrastructure for AI agents, though they implement this functionality differently; Tags unique to letta: llm, self-improvement, memory-system, development-platform; Also covers LLM Frameworks; Use Letta when you need a platform to develop AI agents that can learn and self-improve over time through their interactions. ### When should I choose Memori over letta? Choose Memori over letta when License: Memori is Other, letta is Apache-2.0; Pricing: Pricing details are not explicitly stated in the provided repository content.; Requirements: The tool requires set up of an API key for Memori and your LLM; Both Letta and Memori provide memory infrastructure for AI agents, though they implement this functionality differently; Tags unique to Memori: stateful, memory-management, ai-memory, llm-agnostic; Also covers Model Training; When you need a system to turn agent execution and conversation into structured, persistent state without disrupting your current IT environment. ### When should I avoid letta? Avoid using Letta if your project strictly needs real-time data processing without statefulness; it focuses on agents with memory capabilities which adds to the complexity. Do not use Letta if you are looking for a minimalistic solution since its advanced features and SDK might introduce unnecessary overhead. ### When should I avoid Memori? Avoid if you need a tool that natively extends beyond memory management to include features like autonomous agent navigation or extensive model training utilities, as Memori focuses specifically on AI ### Is letta or Memori more popular on GitHub? letta has more GitHub stars (23,708 vs 15,549). Stars measure visibility, not whether either tool fits your constraints. ### Are letta and Memori open source? Yes - both are open-source projects on GitHub (letta: Apache-2.0, Memori: Other). ### Where can I find alternatives to letta or Memori? GraphCanon lists graph-backed alternatives at /tools/letta-ai-letta/alternatives and /tools/memorilabs-memori/alternatives (/tools/letta-ai-letta/alternatives.md, /tools/memorilabs-memori/alternatives.md), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at /compare/letta-ai-letta-vs-memorilabs-memori.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, letta or Memori? letta: Very active. Memori: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for letta and Memori? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: letta: /tools/letta-ai-letta/trust; Memori: /tools/memorilabs-memori/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=letta-ai-letta`](/api/graphcanon/graph?tool=letta-ai-letta) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_