What is Memori?
Stop repeating yourself to your AI agents. Memori is an open-source memory intelligence engine designed for developers, giving your AI applications a human-like ability to remember context, preferences, and relationships across conversations. This eliminates the need to constantly provide backstory, resulting in smarter, more efficient, and truly personalized AI experiences.
Key Features
🧠 Dual-Mode Memory Architecture Memori introduces a unique system that mimics human memory patterns. Conscious Mode acts like a short-term working memory, automatically promoting essential details for immediate access. Auto Mode provides dynamic, intelligent search across your entire knowledge base, ensuring no relevant detail is missed. You can also combine them for the most comprehensive context retrieval.
🔌 Universal, One-Line Integration Integrate persistent memory into your project with a single line of code: memori.enable(). Memori is built to work with any LLM library you already use, including OpenAI, Anthropic, and LiteLLM, automatically recording and contextualizing all conversations without requiring you to refactor your existing code.
🤖 Sophisticated Multi-Agent System Behind the scenes, Memori operates with a three-layer intelligence architecture. A dedicated Memory Agent processes every conversation, a Conscious Agent analyzes patterns to identify and promote key information, and a Retrieval Agent intelligently selects the most relevant context for injection. This ensures memory is not just stored, but understood.
🗂️ Structured and Flexible Memory Types Go beyond simple conversational history. Memori organizes information into four distinct types: Short-term for recent context, Long-term for permanent insights and preferences, Rules for user-defined constraints (e.g., "I prefer clean code"), and Entity memory for dynamically tracking people, projects, and relationships.
Use Cases
Intelligent Customer Support: Build a support bot that remembers a customer's entire interaction history across multiple sessions. It can instantly recall past issues, product preferences, and previous solutions, allowing you to provide fast, context-aware service without asking the user to repeat themselves.
Personalized E-Commerce Assistants: Create a smart shopping assistant that genuinely knows its customers. Memori tracks preferences, past purchases, and browsing habits to offer tailored recommendations that feel personal and relevant, significantly improving user experience and conversion rates.
High-Performance Development Aides: Equip your internal coding assistants with a perfect memory of your project's architecture. It can remember that you use FastAPI with PostgreSQL, prefer microservices, and work with a teammate named Mike, providing perfectly contextualized code suggestions and solutions every time.
Conclusion
Memori provides the essential memory layer your AI agents have been missing. By automating context retention and retrieval with a sophisticated, human-like architecture, you can focus on building powerful applications instead of managing conversational state.
Explore the GitHub repository to see how Memori can enhance your projects.
Frequently Asked Questions (FAQ)
1. How difficult is it to integrate Memori into an existing project? Integration is designed to be exceptionally simple. After installing the SDK (pip install memorisdk), you can enable universal memory recording for all your LLM calls with just two lines of Python code. It works out of the box with major libraries, so no complex refactoring is needed.
2. Is Memori just another vector database for conversations? No. While it uses robust database infrastructure (supporting SQLite, PostgreSQL, and MySQL), Memori is a complete memory intelligence system. Its multi-agent architecture actively analyzes, promotes, and categorizes information into distinct memory types (short-term, long-term, rules, entities), providing a far more structured and nuanced context than simple semantic search over a vector store.
3. Can Memori handle memory for multiple different users or applications securely? Yes. Memori includes built-in namespace separation, making it suitable for multi-tenant applications. You can create isolated memory spaces for different users, clients, or projects, ensuring that context is never shared or leaked between them.
More information on Memori
Launched
2023-07
Pricing Model
Free
Starting Price
Global Rank
Follow
Month Visit
<5k
Tech used
Memori was manually vetted by our editorial team and was first featured on 2025-08-20.
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