nikita-rulenko/Helixir

First causal agentic AI memory

49
/ 100
Emerging

This project gives AI agents a long-term memory that understands connections between facts, rather than just recalling isolated pieces of text. It takes natural language input from an AI agent's conversations, extracts specific facts, preferences, and goals, and stores them in a structured way. This helps AI agents like those used in AI assistants or automated customer service remember past interactions, individual user preferences, and even their own learning over time, making conversations more coherent and personalized.

Use this if you need an AI agent to remember past interactions, preferences, and decisions across different conversations, and perform causal reasoning based on this stored knowledge.

Not ideal if your AI agent only needs to recall information from the current conversation or you only require simple keyword or semantic search without understanding the relationships between pieces of information.

AI-assistant-memory conversational-AI intelligent-agents personalization knowledge-representation
No Package No Dependents
Maintenance 10 / 25
Adoption 9 / 25
Maturity 13 / 25
Community 17 / 25

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Stars

74

Forks

14

Language

Rust

License

MIT

Last pushed

Feb 19, 2026

Commits (30d)

0

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