OpenMemory
OpenMemory is a Chrome extension that adds a universal memory layer to browser-based AI tools, capturing context from your interactions with ChatGPT, Claude, Perplexity and more so every AI picks up right where you left off. It auto-loads your preferences, project setups, progress notes, and custom instructions across sessions and platforms, enriching prompts with context-rich snippets to deliver more personalized, relevant responses. With one-click sync from ChatGPT, you preserve existing memories and make them available everywhere, while granular controls let you view, edit, or disable memories for specific tools or sessions. Designed as a lightweight, secure extension, it ensures seamless cross-device synchronization, integrates with major AI chat interfaces via a simple toolbar, and offers workflow templates for use cases like code reviews, research note-taking, and creative brainstorming.
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MemMachine
An open-source memory layer for advanced AI agents. It enables AI-powered applications to learn, store, and recall data and preferences from past sessions to enrich future interactions. MemMachine’s memory layer persists across multiple sessions, agents, and large language models, building a sophisticated, evolving user profile. It transforms AI chatbots into personalized, context-aware AI assistants designed to understand and respond with better precision and depth.
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Papr
Papr is an AI-native memory and context intelligence platform that provides a predictive memory layer combining vector embeddings with a knowledge graph through a single API, enabling AI systems to store, connect, and retrieve context across conversations, documents, and structured data with high precision. It lets developers add production-ready memory to AI agents and apps with minimal code, maintaining context across interactions and powering assistants that remember user history and preferences. Papr supports ingestion of diverse data including chat, documents, PDFs, and tool data, automatically extracting entities and relationships to build a dynamic memory graph that improves retrieval accuracy and anticipates needs via predictive caching, delivering low latency and state-of-the-art retrieval performance. Papr’s hybrid architecture supports natural language search and GraphQL queries, secure multi-tenant access controls, and dual memory types for user personalization.
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EverMemOS
EverMemOS is a memory-operating system built to give AI agents continuous, long-term, context-rich memory so they can understand, reason, and evolve over time. It goes beyond traditional “stateless” AI; instead of forgetting past interactions, it uses layered memory extraction, structured knowledge organization, and adaptive retrieval mechanisms to build coherent narratives from scattered interactions, allowing the AI to draw on past conversations, user history, or stored knowledge dynamically. On the benchmark LoCoMo, EverMemOS achieved a reasoning accuracy of 92.3%, outperforming comparable memory-augmented systems. Through its core engine (EverMemModel), the platform supports parametric long-context understanding by leveraging the model’s KV cache, enabling training end-to-end rather than relying solely on retrieval-augmented generation.
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